economic genocide in the post-communist countries? the new ... · post-communist countries? the new...

Economic Genocide in the Post-Communist Countries?

The New Insights from Russian Towns

Alexi Gugushvili

With the Research Team headed by

Professor Larry King

Department of Sociology

University of Cambridge

[email protected]

mailto:[email protected]

Privatization and Mortality

“Mass Privatization and the Postcommunist Mortality Crisis” in The

Transformation of State Socialism: System Change, Capitalism or Something

Else (2007). (Lawrence King and David Stuckler) Edited by David Lane. Palgrave. Pp. 179-197. 2007.

Reprinted in Russian in “Massovaya privatizatsiya i krizis smertnosti v postkommunisticheskikh stranakh.” Mir Rossii Sotsiologiia. (Russian Sociology). June 2007, 16(3): 112-136.

“Rapid Large-Scale Privatization and Death Rates in Ex-Communist Countries: an analysis of stress-related and health system mechanisms.” (Lawrence King, David Stuckler and Patrick Hamm) 2009. International Journal of Health Services. Volume 39 (3): 461-489.

“Mass privatisation and the post-communist mortality crisis: a cross-national analysis” (David Stuckler, Larry King and Martin McKee). 2009. The Lancet. Jan. 31, Vol. 373, No. 9661: 399-407.

Reported in the New York Times, Financial Times, Economist, BBC radio, NPR

and many other outlets globally. Comment by Sir Michael Marmot and Martin

Bobak in The Lancet Jan.15, 2009.

Comment posted by Joseph Stiglits on NYT website. Debate with Jeffrey Sachs in Financial Times. Comment on media coverage of the findings in British Journal of Medicine.

Post-Communist Mortality Crisis

“Despite economists’ reputation for never being

able to agree on anything, there is a striking degree

of unanimity in the advice that has been provided to

the nations of Eastern Europe and the former Soviet

Union (FSU). The legions of economists who have

descended on the formerly Communist economies

have provided advice very similar …. The three

“-ations”—privatization, stabilization, and liberalization

—must all be completed as soon as possible.”

Lawrence Summers (1994: 252-253)

Theories of Privatization

Neoliberal Theory

• Policy innovation: Mass Privatization - private ownership superior to state ownership

• More important political logic:

1. privatization eliminates the power base of the communists, and

2. must privatize during the “exceptional period” when there was a window of opportunity before anti-reform coalition of managers and workers in SOEs forms

Neoclassical Sociological Theory

• Mass Privatization destroys firms creating a vicious circle of firm and state failure resulting in “patrimonial capitalism”

• Strategic ownership via competitive ownership after state-sponsored restructuring is the best way to privatize, creating “liberal capitalism”

Possible Mechanisms Linking Mass Privatization and Increased Mortality

Privatization Unemployment Stress Mortality

Privatization Loss of firm provided Mortality

medical care

Privatization Loss of firm provided Stress Mortality

social consumption

Privatization Firm failure Stress Mortality

Economic decline Mortality

Privatization Fiscal crisis/state failure Stress Mortality

Less health spending Mortality

Increased violence Mortality

Privatization Inequality Status loss Mortality

68

69

70

71

Life

Expecta

ncy a

t B

irth

(yea

rs)

1991 1994 1997 2000Year

Mass Privatizers Non Mass Privatizers

Data Source: WHO European Health for All Database 2007

Postcommunist Countries

Mass Privatization and Life Expectancy

68

69

70

71

Life

Exp

ecta

ncy a

t B

irth

(ye

ars

)

1991 1994 1997 2000Year





Mass Privatization

Begins in Russia

’98 Russian Financial Crisis

(Per Capita GDP drops 30%)

Total of 112,625 State-

owned Enterprises

Privatized (over 50%)

Total of 644 State-

owned Enterprises

Privatized (less 10%)

Mass Privatization and the Postcommunist Mortality Crisis

David Stuckler1, Lawrence King2, and Martin McKee3

December 3rd, 2007

Keywords: post-communist, mortality, privatization 1 University of Cambridge, Department of Sociology, Faculty of Social and Political Sciences and King’s College. E-mail: [email protected] 2 University of Cambridge, Department of Sociology, Faculty of Social and Political Sciences and Emmanuel College. E-mail: [email protected] 3 London School of Hygiene and Tropical Medicine, European Centre on Health of Societies in Transition. E-mail: [email protected]

Word Count (including abstract, w/o references): 3,440

Title: Mass Privatization and the Postcommunist Mortality Crisis

Abstract

Background: During the early-1990s adult mortality rates in almost all Post-communist European countries rose, although there have been striking unexplained differences across countries and over time. While previous studies have suggested the pace of economic transition was a key driver of increased mortality rates, to our knowledge no study has empirically evaluated the role of economic policies. This article tests whether mass privatization, a leading policy instrument used to facilitate rapid economic transition, can account for differences in adult mortality trends in Post-communist European countries.

Methods: We used multivariate longitudinal regression to analyse male working-age mortality rates in Post-communist countries of Eastern European and the former Soviet Union from 1991 to 2002. To isolate the effect of mass privatization, models control for price and trade liberalization, income change, initial country conditions, structural predispositions to higher mortality and other potential confounders.

Findings: Mass privatization programs, defined as transferring at least 25% of large-state owned enterprises to the private sector in a two year period, was associated with an increase of 18.4% in short-term adult male mortality (95% CI: 12.4% to 24.5%), with similar results using the alternative privatization indices from the European Bank for Reconstruction and Development. The speed of privatization, was more strongly associated with mortality increase than was its scale.. One mediating factor may be male unemployment , which was increased substantially by mass privatization (69%, 95% CI: 43% to 94%). The effect of mass privatization on mortality is mitigated at greater levels of social capital and becomes insignificant when more than 45% of a population is a member of at least one social organization.

Interpretation: Rapid mass privatization as an economic transition strategy was a critical determinant ofadult male mortality trends in Post-communist countries, and this effect is mediated by a country’s level of social capital. These findings may be relevant to other countries where similar policies are being considered.

Introduction

One of the most profound modern social experiments has been the transition from communism to capitalism in Europe and Central Asia during the early- to mid-1990s. Political, economic and social institutions have undergone related transformations and there have been marked swings in income levels and in mortality. Unarguably, these transitions have had unprecedented consequences for health: the United Nations attributes over three million premature deaths to transition, UNICEF estimates over ten million “missing men” due to system change, and at the time of writing, more than fifteen years after these transitions began, only a little over half of the ex-communist countries have re-gained their pre-transition life expectancy levels.1-3 But were these excess deaths inevitable?

It is unlikely. Not all countries have fared so poorly: while Russia, an extreme case, lost nearly five years of life expectancy between 1991 and 1994, Croatia and Poland saw steady improvements of almost one year of life expectancy during this same period. Table 1 depicts the substantial variation in mortality rate trends between the “best-five performing” and the “worst-five performing” countries in terms of male adult mortality rate changes, which range from a fall of 6.7% in the best countries to an increase of 25.8% in the worst.

[Table 1 about here]

What accounts for these differences in the pace of change in mortality rates across countries and over time? The public health literature, where the mortality crisis has been most extensively studied, has largely focused on proximal and intermediate health determinants and, in particular, on the major role played by hazardous alcohol consumption in these changes4-6, superimposed on a high underlying mortality that also reflects poor diet and, in men, high rates of smoking.7 However, less is known about why there have been changes in, for example, hazardous drinking in different countries at different times. Research comparing Russian regions has identified the pace of transition, assessed by measures such as job gains and losses, as an important factor,8 9 but there is little work that attempts to both theorize and empirically evaluate the effects on health of the underlying policies pursued by governments and, as a result, the wider determinants of the mortality patterns across the post-Soviet world.

One answer, we suggest, lies in the economic strategies that countries used to build capitalism out of communism.

Shock Therapy and the Neo-liberal Policy Advisors

[[I would try to follow Popov’s example in not emphasising the role of external advisors. You risk cheapening the argument if you make the tragic Russian experience into a kind of theatre in which outsiders conduct domestic ideological arguments. It is unappealing. More disciplined language would, I think, be better received.

(That said I rather like Stiglitz’s ironic description of them as ‘market Bolsheviks’ (xxii)– and Gorbachev also made comparisons with the Bolsheviks ‘yet another attempt to force Russia into utopia, utilizing once again the Bolsheviks' methods of "shoving down the throat." (xv) (Gorbachev’s Foreword and Stiglitz’s Preface in: Klein LR and Pomer M, editors. The new Russia. Transition gone awry. Stanford, CA: Stanford University Press; 2001.)

It would appear in any case that there was a large element of ‘endogeneity’ in the liberalisation process – Popov, Stiglitz etc.]]

On one side, there was a group of radically free-market advisors, led by Jeffrey Sachs, who argued that capitalist transition needed to occur as rapidly as possible.10-14 They argued that if reforms were delayed, the former communist countries would only make it halfway to capitalism, instead ending up with an inadequate type of market socialism or even returning to communism.

The prescribed policy was called “shock therapy,” involving three major elements: liberalization of prices and trade to allow markets to re-allocate resources, stabilization programs to suppress inflation, and the mass privatization of state-owned enterprises to create appropriate incentives. When implemented simultaneously these would cause an irreversible shift to a market-based economy. While liberalization and stabilization had been implemented before in countries throughout Asia and Latin America, the rapid transfer of state owned companies to the private sector on such a massive scale was without precedent and, even now, many sectors in those regions remain in state ownership.15 16

Nonetheless, according to Sachs, “The need to accelerate privatization is the paramount economic policy issue facing Eastern Europe. If there is no breakthrough in the privatization of large enterprises in the near future, the entire process could be stalled for years to come. Privatization is urgent and politically vulnerable.”17

[[If you are going to retain this emphasis on foreign advisors you need to produce some evidence that their advice was decisive to the adoption of the policies.]]

Gradualists and the Institutionalist Critique

In the other camp were the gradualists or institutionalists. They argued that capitalism could not be created overnight simply by obliterating all institutions of the Communist economy, pointing out that capitalism only emerged over several centuries in Western Europe. The gradualists therefore called for a slower transition, recommending that countries gradually phase in markets and private property while allowing time to develop institutions needed to make markets work well.18-22 They advocated a dual-track market-planning system so that former communist countries would incrementally “grow out of the plan” with the private sector eventually outgrowing the state-owned sector – much like what is occurring in China today.

In most countries the shock therapists won the day. Their policies were fully implemented in Russia by 1994, and most countries implemented some or all of them by the mid-1990s although the greatest variation was in privatization.1 23 Just how radical these policies have been can be seen by comparison with Margaret Thatcher, the “great privatizer”, who during her 11-year tenure in Britain privatized approximately 30 state enterprises, with Yeltsin’s regime in Russia which, under the guidance of the shock therapists [[It is not clear here, whether this is intended to refer to domestic or foreign therapists or both. It would be more honest to be clear about this.]] , privatized over 15,000 large state-owned Russian firms between 1992 and 1994. The scale of privatization in the former communist countries has been by far the greatest in history.

Relationships between Mass Privatization and Life Expectancy

Has rapid privatization had an effect on mortality rates? Because rapidly privatizing thousands of inefficient Soviet-era firms would shed many jobs before new firms would have had emerged to absorb those who were dislocated, it might be expected that the resultant short-term increases in unemployment would lead to short-term increases in adult mortality rates, given evidence from other settings of the effects of unemployment on the health of the individuals affected.24-27

[[These citations are selective. Although unemployment is harmful at the individual level, mortality in western countries tends to rise when unemployment falls because of the other harmful effects of economic upturns (eg Gerdtham UG, Ruhm CJ. Deaths rise in good economic times: Evidence from the OECD. Economics & Human Biology 2006; 4 (3) : 298-316.)

Of course individual level associations in Western countries might be the better basis for predicting the effects of massive increases in unemployment. Hence the suggested rewording.]]

Rapid Privatization Systematic Unemployment Increased Adult Mortality

The consequences would be most severe for employees of large-scale capital-intensive heavy industry and manufacturing enterprises. Of all firms, the large enterprises would be the least equipped to successfully compete in new market conditions and, because of their greater inefficiency and technological “backwardness”, suffer the greatest job losses while being the least able to offer their employees, few of whom had transferable skills, reasonable chances for success in finding new jobs.

Figure 1 compares male life expectancy trends for the countries that implemented mass privatization programs for large state enterprises (defined as a program that transferred the ownership of at least 25% of large-state [[???]] owned enterprises to the private sector in a two year period by selling them with citizen vouchers and giveaways to firm insiders) versus those that did not. Overall, those countries that pursued mass privatization in the early- to mid-1990s experienced sharp drops in life expectancy; in those that did not, life expectancy also dipped modestly but then steadily improved. Unemployment rates followed a similar trend: increases were dramatic in countries that privatized rapidly but much more modest in countries that privatized more slowly (Table 1). Four out of the five worst countries, in terms of life expectancy, had implemented mass privatization whereas only one of the five best performers had done so.

[Figure 1 about here]

In the rest of this paper we test the hypothesis that the implementation of mass privatization programs accounts for differences in mortality increases in post-communist countries.

Data and Methods

Our data on international male mortality rates [[be more specific about metric]], which cover 25 post-communist countries from 1991 to 2002, are taken from the UNICEF Monitoring Transition in Central & Eastern Europe Database.28 While there have problems with mortality data from some countries in this region, these relate mainly to deaths in infancy and childhood,29 detailed attribution of specific causes of death,30 and data from periods of civil conflict.31 The consensus among scholars of mortality data in transition countries has been that aggregate rates of all-cause adult mortality are sufficiently valid and reliable to permit comparative studies.6 32-36

We measure rapid economic transition policies in two ways: first, using a dummy variable for whether a country implemented a mass privatization program, as defined previously (0 prior to mass privatization, 1 thereafter); and second, by using EBRD privatization indices of progress in privatization (ranging from 1 – “planned” to 4.3 – “advanced market economy”) (Table 2).37

An issue with the EBRD privatization indices is that the main policy advisors at the EBRD backing the shock therapists were also those responsible for scoring progress in privatization. Since coding occurred after country performance had been observed, there might be ideological pressure to code more successful countries as being more radical reformers. According to the EBRD, the privatization codings “reflect the judgment of the EBRD’s Office of the Chief Economist about country-specific progress in transition.”37

Our measure of mass privatization program implementation overcomes the observer biases and subjectivity in the EBRD indices. The EBRD Transition Report Series describes when countries implemented privatization program, how many firms were privatized under them, and by what method this privatization was accomplished.38 We use this data to code a large jump as a 25% transfer, which corresponds to a jump from one to three on the EBRD large-scale privatization index scale. Since the correlations between the EBRD large-scale index and small-scale index are statistically indistinguishable by our analysis (r=0.97 in Russia, for example), we proceed using an average of the large- and small-scale indices to reduce measurement errors.


We adjust for Log GDP per capita to control for income level , which is strong and robust determinant of health. [[In the long run. Short term movements at population level are often in opposite directions eg ref above Gerdtham ]] We also control for political changes with a widely used index of democratization from Freedom House because, given the known [[??]] association between democracy

[[You should be more specific about the index used. Is it the index for ‘Political rights’? if so say so. I would agree that this is a reasonably good proxy for democracy. The civil liberties index will be more weakly associated with democracy at a global level eg Singapore, Hong Kong, Brunei. Whether or not ‘democracy’ associates strongly with health levels depends very much on what else is in the model. If one uses the World Bank’s governance indicators and distinguish democracy (‘voice and accountability’) from civil liberty and state effectiveness in fairly inclusive datasets then state effectiveness soaks up most of the variance – as anyone reflecting on recent global mortality trends might suspect: eg the outstanding performance of well governed non-democratic countries such as Singapore, Hong Kong, Brunei, Oman etc. For a view contrary to yours on democracy and health see: Horton R. REFLECTING ON HEALTH CHALLENGES: Remarks for the Official Launch of WHO's Commission on Social Determinants of Health. http://www.who.int/social_determinants/speech/en/print.html.

There is also perhaps an inconsistency between favouring an emphasis on the quality of institutions to account for the course and effects on well being of economic transformations and ignoring the qualitative performance of state institutions in the political sphere. ]]

and life expectancy39 these changes might confound the relationship between the economic changes and health. To isolate the effect of privatization we control for price and trade liberalization, the main complementary policies recommended by the shock therapists. War affects reporting of mortality, so we use a dummy for the occurrence of military or ethnic conflict. The population dependency ratio, which measures the ratio of total working-age adults to elderly and infants, controls for the proportional size of the workforce and the relative cost of state social welfare systems. We also control for demographic characteristics using urbanization ratios and population tertiary education rates.

As we are interested primarily in fluctuations in mortality, our regression models also use a set of country dummy variables to net out relatively fixed aspects of national surveillance infrastructure, initial country conditions and predispositions to higher mortality [I presume these are country specific slopes … is that correct? It might help the less numerate (like me) to make sense of it if it was described this way]]. In effect, this makes the data more comparable. Country dummy variables also effectively hold constant possibly confounding geographic effects such as proximity to Western Europe or membership of the former Soviet Union as well as some of the potential coding bias in the World Bank privatization indices.

Thus our model is

AMRit = α + βPRIVit + βGDPit + βLIBit + βTRADEit + βDEMit + βWARit + βDEPit + βEDUCit + μi +εit

Here i is country and t is year, AMR is logged adult male mortality rates (working ages of 15 to 59), PRIV is one of the two privatization measures, GDP is log GDP per capita in constant US dollars, LIB is the EBRD price liberalization index, Trade is the EBRD foreign exchange and trade liberalization index, DEM is the democratization index, WAR is a dummy for military conflict, EDUC is the percentage of population with tertiary education, URBAN is the percentage of the population living in urban settings, DEP is the population dependency ratio, μ is a set of country fixed effects, and ε is the error term.

Results

Effect of Mass Privatization on Male Working Age Mortality Rates

Table 3 shows the results of our basic model. Mass privatization programs are associated, on average, with a 12.3% increasein adult male mortality (p<0.001). Compared with the 25.8% increase in the worst performing countries at the peak of the mortality crisis in 1994, this is a substantial association. In our dataset, mass privatization can on average account for roughly half of the mortality rate increases in the worst performing countries and a large fraction of the differences in the mortality rate increases between countries. To further put this effect in perspective, the estimated effect of increasing the rate of economic growth ten-fold would not be enough to offset the increase in mortality rates resulting from mass privatization (β Log GDP per capita = -0.11, p<0.001, not shown). Clearly, even if mass privatization might enhance economic growth, the effect would not be anywhere near this magnitude.


The EBRD privatization index also increases adult mortality rates (4.10%, 95% CI: 1.78% to 6.41%). While our controls hold constant membership of the former Soviet Union, they do not preclude interactions between being in the former Soviet Union and the effects of privatization. If the pace of privatization mattered more than the level of privatization, then the EBRD index should have a greater effect in countries where mass privatization as a transition strategy was more dominant.

This is exactly what we found. When we restrict the sample to Former Soviet Union countries such that changes in the EBRD index more accurately reflect the implementation of mass privatization, variations in the EBRD privatization index are even greater determinants of adult mortality. Each one unit increase, roughly the same as one standard deviation, increases mortality by 10.3%. Since the average change in the privatization index over the entire period was around two units, this amounts to roughly the same effect size as that attributed to our measure of mass privatization implementation and the net effects of the two become statistically indistinguishable.

Do these results offer an explanation of differences in mortality changes in the former Soviet Union? Figure 2 compares the trajectories of Russia, which implemented mass privatization in 1992, with its neighbour Belarus, which adopted a more gradual approach to transition. By 1994, at the peak of Russia’s mortality crisis, Russia had privatized over 112,000 firms or more than half of all Russian state-owned enterprises, while over this same period Belarus only privatized 640 firms, or less than 10% of their state-owned sector. Unemployment rates in both countries started at very similar low levels, but in Russia they increased over 13-times as much as in Belarus; in parallel, mortality rates in Russia increased four times as much as in Belarus (roughly a 11.3% difference in the average mortality rate increase). Our estimate using the EBRD index of a 20.6% increase in mortality rates attributable to privatization in Russia (2 point increase) to a 8.8% estimated for Belarus (0.85 point increase), closely matches the cumulative mortality differences over time between these countries. Similarly, our measure of a mass privatization program estimates a 18.4% increase in adult male mortality rates associated with this policy: this is strikingly close to the observed 17.8% average increase in Russia between 1992 and 1994.


Effect of Mass Privatization on Unemployment Rates

We now attempt to bridge the cross-national privatization results and the public health findings by testing privatization’s relationship to unemployment. Privatization has significant and pronounced effects: implementing mass privatization increases unemployment by 69% compared to countries where the process was more gradual. In the full country sample the effect of a one unit increase in the EBRD index was 46% and for the former Soviet Union sample the effect was again larger at 68%. This reiterates that rapid mass privatization caused more job losses than slower privatization, most likely because it provided fewer opportunities for firms to adapt and stay financially solvent.

A major caveat in using the International Labor Office unemployment data is that they reflect registered unemployment levels which are much lower than actual unemployment levels. Despite this limitation, the results provides evidence of the mechanism by which privatization effected increased mortality. The models also net out much of the bias by evaluating changes within countries over time. It is also difficult to imagine how variations in the propensity to register for unemployment alone could account for these trends. To the extent they might, it runs against our hypothesis: areas with the most privatization had the least adequate social safety nets because privatization, by design, critically hampered the state’s revenue base. This means that in countries where more privatization occurred people would have had less incentive to register for unemployment, so any residual bias renders our estimates extremely conservative.

Interaction between Social Capital and Rapid Privatization

If dislocation serves as a key mechanism linking rapid privatization to increased mortality rates, then it might be expected that rapid privatization’s adverse effects would be in part mitigated in countries which had more inclusive social policies or higher levels of social cohesion. Figure 3 shows the results of a regression model which interacts mass privatization implementation with the percentage of a country’s population who are members of at least one social organizations (such as a labour union, church or religious group, sports club or a political organization) for 18 countries taken from the European World Values Survey (EWVS).40


This shows how the effect of rapid mass privatization on adult mortality rates linearly decreases with increasing social capital. In fact, in countries where more than 45% of the population was a member of a social organization, mass privatization had no significant adverse effect. Since social capital does not change greatly over time, this measure is almost surely acting as an effect modifier rather than a confounder in our models. This finding may help to explain why mass privatization programs in the Czech Republic, which had the second highest social membership (48%, equal to Western Europe’s average level) of all the former communist countries, had no significant negative effect, but in the former Soviet countries, where social membership was much lower (~10%), rapid privatization had extremely adverse consequences. Other measures of social capital from the EWVS such as trust produce similar results (not shown).

Robustness Checks

We have performed a series of robustness checks. First we removed the complementary transition policies, including price liberalization and trade liberalization, and also added period dummies and indicators for stabilization programs. None of the mortality results was significantly affected. Since most mass privatization programs were implemented in the span of two years, we replicated our models using a coding of 0 prior to, 1 during, and 0 after mass privatization: the results were statistically indistinguishable. We also checked our coding with the World Bank economists in charge of mass privatization implementation, who agreed with all of our classifications except for Romania, which they considered an indeterminate case. We re-coded Romania as a non-mass privatizer and found that the overall results were unchanged. We also sequentially removed countries where data are suspected to be misreported, such as the Central Asian and war-torn countries. The results remained consistent and were slightly larger (as found with the former Soviet Union sample). Using alternative estimation procedures, such as first-differences or more advanced methods for adjusting for serial correlation also do not affect our findings. A complementary paper has examined the relationship between privatization and specific causes of death, finding specific associations that are consistent with the known effects of economic transition on health and, in particular, the major role played by alcohol as an immediate cause of rapid changes in mortality.4,5

Discussion

In writing about Stalin’s policies, John Maynard Keynes notes that

“We have a fearful example in Russia today of the evils of insane and unnecessary haste. The sacrifices and losses of transition will be vastly greater if the pace is forced…”76

Today we can witness the same process but in reverse: the new regimes did not call for radical statism but rather for radical privatization to create capitalism.

As Emile Durkheim reminds us,77 any disruption to the established social order creates high levels of anomie, or social stress. Mass privatization is a case-in-point: by rapidly transforming existing enterprises into private property in the absence of a real class of strategic owners, many firms went bankrupt and excess jobs were lost. People were left disoriented without jobs amidst unfamiliar market conditions. While this period was predicted by the shock therapists, who viewed it simply as a period of “resource reallocation”, it had real human costs: even if capital resources could be reconfigured rapidly, people simply are not able do so as quickly. Inclusive social structures during this period appear to have been critically important in counter-balancing the harms of this dislocation, enabling people to cope with social disruptions, a finding consistent with research on the determinants of health at an individual level.78

Our findings are consistent with a considerable body of research on mortality in the post-communist period, which has provided evidence for the role of a number of factors including acute psychosocial stress 6 41-45 46 47 48, abridged access to and declining quality of medical care (much provided at workplaces) 49 50 51 52 53, impoverishment53-55, rapid pace of transition52, increased unemployment 56 57 58, rising social inequalities59 60, social disorganization61, worsened corruption62, and the erosion of social capital 59 63. Although it would be too simple to attribute a direct cause and effect relationship, each of these findings can be linked, in some way, to mass privatization programs.64-75

Did going more slowly hurt the prospects for capitalism? Is Slovenia – one of the more gradual privatizers – any less capitalist than Ukraine? In fact, by approaching transformation rapidly and radically, it appears that prospects for Western-style capitalism may have been seriously impaired in countries like Russia. Slower privatizers manage to reach a capitalist endpoint but did not absorb nearly the same amount of social costs along the road (Table 1).

The policy implications are clear. Great caution should be taken when macro-economic policies seek to radically overhaul the economy without considering potential effects on the population’s health.

[[living conditions. As variants of shock therapy are still discussed for China [[I would remove this reference – see Popov on China and Vietnam ie if Vietnam could cope with shock therapy why couldn’t China? … but in any case there has already been massive ‘quasi-privatisation’.]] , India, Egypt and numerous other developing and middle-income countries – including Iraq – which are just beginning to privatize their large state-owned sectors, the lessons from the transitions from communism should be kept in mind.]]

Figures and Tables

Figure 1. Mass Privatization and Life Expectancy, Postcommunist Countries

Figure 2. Mass Privatization and Adult Mortality Rates in Belarus and Russia

Figure 3. Interaction between Mass Privatization and Social Capital

Table 1. Change in Total Adult Male Mortality Rates and Amount of Privatization, Postcommunist Countries from 1991 to 1994

Table 2. Description of Privatization Measures

Table 3. Effect of Privatization on Adult Male Mortality Rates

Table 4. Effect of Privatization on Male Unemployment Rates



Note: Results presented from the regression model AMRit = α + β1PRIVit + [β2SCi ] + β3PRIVit*SCi + βX + μi +εit. using the estimation sample of countries for which social capital data are available (Number of countries = 18). [∙] denote that the time-invariant social capital term is captured by the country-specific effect, μi; SC is a measure of social capital taken from the European World Values Survey. β1PRIVit = 0.129019 and β3PRIVit*SCi = -0.001898. Clustered standard errors calculated from the robust variance-covariance matrix using the formula √var(β1)+XSCvar(β3)+2XSCcov(β1β3).

Table 1. Change in Total Adult Male Mortality Rates and Amount

of Privatization, Postcommunist Countries from 1991 to 1994

Measure 1991-1994

Best Five Countries Albania, Croatia, Czech

Republic, Poland, Slovenia

Change in Total Adult

Mortality Rates -6.7%

Change in EBRD

Average Privatization

Index

1.1

Change in Male

Unemployment Rates 1.1%

Worst Five Countries Kazakhstan, Kyrgyz

Republic, Latvia, Russia,

Tajikistan


Mortality Rates 25.8%

Change in EBRD


Index

1.6

Change in Male


Note: Geometric means calculated for average percentage changes. Adult mortality rates [[SPECIFY EXACT MEASURE]] are from the UNICEF Monitoring Transition in Central & Eastern Europe Database. Enterprise Bank for Reconstruction and Development (EBRD) average privatization index ranges from 1 – communist to 4.3 – complete market. Unemployment rates are registered unemployment rates from the International Labor Organization, and are presented for 1992 to 1994 due to missing comparative data for 1991.


MEASURE OF

PRIVATIZATION DESCRIPTION OF CODING

Mass Privatization Scale: 0 prior to implementation, 1 thereafter

0 Country did not implement a program that transferred the ownership of at least

25% of large-state owned enterprises to the private sector through vouchers and

give-aways to firm insiders.

1 Country implemented a program that transferred the ownership of at least 25%

of large-state owned enterprises to the private sector through vouchers and give-

aways to firm insiders.

EBRD Small-Scale

Privatization Index†

Scale: 1 to 4, 4* (coded as 4.3)

1 Little progress

2 Substantial share privatized

3 Comprehensive program almost ready for implementation

4 Complete privatization of small companies with tradable ownership rights

4+ Standards and performance typical of advanced industrial economies: no state

ownership of small enterprises; effective tradability of land

EBRD Large-Scale



1 Little private ownership

2 Comprehensive scheme almost ready for implementation; some sales completed

3 More than 25 per cent of large-scale enterprise assets in private hands or in the

process of being privatized (with the process having reached a stage at which the

state has effectively ceded its ownership rights), but possibly with major

unresolved issues regarding corporate governance.

4 More than 50 per cent of state-owned enterprise and farm assets in private

ownership and significant progress on corporate governance of these enterprises.

4+ Standards and performance typical of advanced industrial economies: more than

75 per cent of enterprise assets in private ownership with effective corporate

governance

Note: Mean scores presented for 25 transition countries. † - Variable definitions were originally developed in 1994 but were refined and amended in later reports; Presented definition are quoted directly from the EBRD 1999 Transition Report. “Transition indicator scores reflect the judgment of the EBRD’s Office of the Chief Economist about country-specific progress in transition” (EBRD 2007).


Privatization Measure

Effect on Male Mortality Rates

Ages 15 to 59

All countries Former Soviet

Union

Implementation of Mass

Privatization

12.3%*

(8.6% to 16.0%)

18.4%*

(12.4% to 24.5%)

Implementation of one

unit of average EBRD

privatization

4.1%*

(1.8% to 6.4%)

10.4%*

(6.7% to 14.1%)

Note: Coefficients calculated as semi-elasticities presented; Robust standard errors in parentheses. Models also control for Log GDP per capita, EBRD price liberalization index, EBRD trade liberalization index, democratization, population dependency, the percentage of population living in urban settings, the population education level, and country-specific fixed effects. Number country-years for all countries is 289, number of countries is 24. Number of country-years for the former Soviet Union is 177, number of countries is 15.

Significance at * p<0.001



Effect on Male Unemployment

Rates

All Countries Former Soviet

Union


Privatization

69%*

(43% to 94%)

76%*

(44% to 107%)


unit of EBRD average

privatization

46%*

(31% to 61%)

68%*

(38% to 98%)

Note: Coefficients calculated as semi-elasticities presented; Robust standard errors in parentheses. Models also control for Log GDP per capita, EBRD price liberalization index, EBRD trade liberalization index, democratization, education rate, population dependency, the percentage of population living in urban settings, the population education level, and country-specific fixed effects.

Significance at * p-<0.001

Authors Contributions

DS compiled the data, conducted the empirical analysis and drafted the manuscript; MM oversaw the design of the study, facilitated the interpretation of the findings, and helped draft the manuscript; LK originally conceived of the study, provided background information on the Post-communist context, and guided the overall direction of the analysis.

Funding

MM’s work in transition countries is supported by the European Observatory on Health Systems and Policies and the Wellcome Trust.

Acknowledgement

The authors would like to thank Erica Richardson for assistance on, and comments and criticisms of, various drafts of this paper.

Conflict of Interest Statement

None declared

DS had full access to all the data in the study and final responsibility for the decision to submit for publication.

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68

69

70

71

Life

Exp

ecta

ncy a

t B

irth

(ye

ars

)

1991 1994 1997 2000Year





50

06

00

70

08

00

90

01

00

0

Adult W

ork

ing A

ge M

ort

alit

y R

ate

s

(per

100,0

00 p

opula

tion)

1989 1992 1995 1998 2001Year

Russia Belarus


Belarus and Russia

Mass Privatization and Adult Mortality Rates

Mass Privatization

Begins in Russia

’98 Russian Financial Crisis

(Per Capita GDP drops 30%)

Total of 112,625 State-

owned Enterprises

Privatized (over 50%)

Total of 644 State-owned

Enterprises Privatized

(less 10%)

Mass Privatization and the Postcommunist Mortality Crisis

David Stuckler1, Lawrence King2, and Martin McKee3

December 3rd, 2007

Keywords: post-communist, mortality, privatization 1 University of Cambridge, Department of Sociology, Faculty of Social and Political Sciences and King’s College. E-mail: [email protected] 2 University of Cambridge, Department of Sociology, Faculty of Social and Political Sciences and Emmanuel College. E-mail: [email protected] 3 London School of Hygiene and Tropical Medicine, European Centre on Health of Societies in Transition. E-mail: [email protected]

Word Count (including abstract, w/o references): 3,440

Title: Mass Privatization and the Postcommunist Mortality Crisis

Abstract

Background: During the early-1990s adult mortality rates in almost all Post-communist European countries rose, although there have been striking unexplained differences across countries and over time. While previous studies have suggested the pace of economic transition was a key driver of increased mortality rates, to our knowledge no study has empirically evaluated the role of economic policies. This article tests whether mass privatization, a leading policy instrument used to facilitate rapid economic transition, can account for differences in adult mortality trends in Post-communist European countries.

Methods: We used multivariate longitudinal regression to analyse male working-age mortality rates in Post-communist countries of Eastern European and the former Soviet Union from 1991 to 2002. To isolate the effect of mass privatization, models control for price and trade liberalization, income change, initial country conditions, structural predispositions to higher mortality and other potential confounders.

Findings: Mass privatization programs, defined as transferring at least 25% of large-state owned enterprises to the private sector in a two year period, was associated with an increase of 18.4% in short-term adult male mortality (95% CI: 12.4% to 24.5%), with similar results using the alternative privatization indices from the European Bank for Reconstruction and Development. The speed of privatization, was more strongly associated with mortality increase than was its scale.. One mediating factor may be male unemployment , which was increased substantially by mass privatization (69%, 95% CI: 43% to 94%). The effect of mass privatization on mortality is mitigated at greater levels of social capital and becomes insignificant when more than 45% of a population is a member of at least one social organization.

Interpretation: Rapid mass privatization as an economic transition strategy was a critical determinant ofadult male mortality trends in Post-communist countries, and this effect is mediated by a country’s level of social capital. These findings may be relevant to other countries where similar policies are being considered.

Introduction

One of the most profound modern social experiments has been the transition from communism to capitalism in Europe and Central Asia during the early- to mid-1990s. Political, economic and social institutions have undergone related transformations and there have been marked swings in income levels and in mortality. Unarguably, these transitions have had unprecedented consequences for health: the United Nations attributes over three million premature deaths to transition, UNICEF estimates over ten million “missing men” due to system change, and at the time of writing, more than fifteen years after these transitions began, only a little over half of the ex-communist countries have re-gained their pre-transition life expectancy levels.1-3 But were these excess deaths inevitable?

It is unlikely. Not all countries have fared so poorly: while Russia, an extreme case, lost nearly five years of life expectancy between 1991 and 1994, Croatia and Poland saw steady improvements of almost one year of life expectancy during this same period. Table 1 depicts the substantial variation in mortality rate trends between the “best-five performing” and the “worst-five performing” countries in terms of male adult mortality rate changes, which range from a fall of 6.7% in the best countries to an increase of 25.8% in the worst.


What accounts for these differences in the pace of change in mortality rates across countries and over time? The public health literature, where the mortality crisis has been most extensively studied, has largely focused on proximal and intermediate health determinants and, in particular, on the major role played by hazardous alcohol consumption in these changes4-6, superimposed on a high underlying mortality that also reflects poor diet and, in men, high rates of smoking.7 However, less is known about why there have been changes in, for example, hazardous drinking in different countries at different times. Research comparing Russian regions has identified the pace of transition, assessed by measures such as job gains and losses, as an important factor,8 9 but there is little work that attempts to both theorize and empirically evaluate the effects on health of the underlying policies pursued by governments and, as a result, the wider determinants of the mortality patterns across the post-Soviet world.

One answer, we suggest, lies in the economic strategies that countries used to build capitalism out of communism.

Shock Therapy and the Neo-liberal Policy Advisors

[[I would try to follow Popov’s example in not emphasising the role of external advisors. You risk cheapening the argument if you make the tragic Russian experience into a kind of theatre in which outsiders conduct domestic ideological arguments. It is unappealing. More disciplined language would, I think, be better received.

(That said I rather like Stiglitz’s ironic description of them as ‘market Bolsheviks’ (xxii)– and Gorbachev also made comparisons with the Bolsheviks ‘yet another attempt to force Russia into utopia, utilizing once again the Bolsheviks' methods of "shoving down the throat." (xv) (Gorbachev’s Foreword and Stiglitz’s Preface in: Klein LR and Pomer M, editors. The new Russia. Transition gone awry. Stanford, CA: Stanford University Press; 2001.)

It would appear in any case that there was a large element of ‘endogeneity’ in the liberalisation process – Popov, Stiglitz etc.]]

On one side, there was a group of radically free-market advisors, led by Jeffrey Sachs, who argued that capitalist transition needed to occur as rapidly as possible.10-14 They argued that if reforms were delayed, the former communist countries would only make it halfway to capitalism, instead ending up with an inadequate type of market socialism or even returning to communism.

The prescribed policy was called “shock therapy,” involving three major elements: liberalization of prices and trade to allow markets to re-allocate resources, stabilization programs to suppress inflation, and the mass privatization of state-owned enterprises to create appropriate incentives. When implemented simultaneously these would cause an irreversible shift to a market-based economy. While liberalization and stabilization had been implemented before in countries throughout Asia and Latin America, the rapid transfer of state owned companies to the private sector on such a massive scale was without precedent and, even now, many sectors in those regions remain in state ownership.15 16

Nonetheless, according to Sachs, “The need to accelerate privatization is the paramount economic policy issue facing Eastern Europe. If there is no breakthrough in the privatization of large enterprises in the near future, the entire process could be stalled for years to come. Privatization is urgent and politically vulnerable.”17

[[If you are going to retain this emphasis on foreign advisors you need to produce some evidence that their advice was decisive to the adoption of the policies.]]

Gradualists and the Institutionalist Critique

In the other camp were the gradualists or institutionalists. They argued that capitalism could not be created overnight simply by obliterating all institutions of the Communist economy, pointing out that capitalism only emerged over several centuries in Western Europe. The gradualists therefore called for a slower transition, recommending that countries gradually phase in markets and private property while allowing time to develop institutions needed to make markets work well.18-22 They advocated a dual-track market-planning system so that former communist countries would incrementally “grow out of the plan” with the private sector eventually outgrowing the state-owned sector – much like what is occurring in China today.

In most countries the shock therapists won the day. Their policies were fully implemented in Russia by 1994, and most countries implemented some or all of them by the mid-1990s although the greatest variation was in privatization.1 23 Just how radical these policies have been can be seen by comparison with Margaret Thatcher, the “great privatizer”, who during her 11-year tenure in Britain privatized approximately 30 state enterprises, with Yeltsin’s regime in Russia which, under the guidance of the shock therapists [[It is not clear here, whether this is intended to refer to domestic or foreign therapists or both. It would be more honest to be clear about this.]] , privatized over 15,000 large state-owned Russian firms between 1992 and 1994. The scale of privatization in the former communist countries has been by far the greatest in history.

Relationships between Mass Privatization and Life Expectancy

Has rapid privatization had an effect on mortality rates? Because rapidly privatizing thousands of inefficient Soviet-era firms would shed many jobs before new firms would have had emerged to absorb those who were dislocated, it might be expected that the resultant short-term increases in unemployment would lead to short-term increases in adult mortality rates, given evidence from other settings of the effects of unemployment on the health of the individuals affected.24-27

[[These citations are selective. Although unemployment is harmful at the individual level, mortality in western countries tends to rise when unemployment falls because of the other harmful effects of economic upturns (eg Gerdtham UG, Ruhm CJ. Deaths rise in good economic times: Evidence from the OECD. Economics & Human Biology 2006; 4 (3) : 298-316.)

Of course individual level associations in Western countries might be the better basis for predicting the effects of massive increases in unemployment. Hence the suggested rewording.]]

Rapid Privatization Systematic Unemployment Increased Adult Mortality

The consequences would be most severe for employees of large-scale capital-intensive heavy industry and manufacturing enterprises. Of all firms, the large enterprises would be the least equipped to successfully compete in new market conditions and, because of their greater inefficiency and technological “backwardness”, suffer the greatest job losses while being the least able to offer their employees, few of whom had transferable skills, reasonable chances for success in finding new jobs.

Figure 1 compares male life expectancy trends for the countries that implemented mass privatization programs for large state enterprises (defined as a program that transferred the ownership of at least 25% of large-state [[???]] owned enterprises to the private sector in a two year period by selling them with citizen vouchers and giveaways to firm insiders) versus those that did not. Overall, those countries that pursued mass privatization in the early- to mid-1990s experienced sharp drops in life expectancy; in those that did not, life expectancy also dipped modestly but then steadily improved. Unemployment rates followed a similar trend: increases were dramatic in countries that privatized rapidly but much more modest in countries that privatized more slowly (Table 1). Four out of the five worst countries, in terms of life expectancy, had implemented mass privatization whereas only one of the five best performers had done so.


In the rest of this paper we test the hypothesis that the implementation of mass privatization programs accounts for differences in mortality increases in post-communist countries.

Data and Methods

Our data on international male mortality rates [[be more specific about metric]], which cover 25 post-communist countries from 1991 to 2002, are taken from the UNICEF Monitoring Transition in Central & Eastern Europe Database.28 While there have problems with mortality data from some countries in this region, these relate mainly to deaths in infancy and childhood,29 detailed attribution of specific causes of death,30 and data from periods of civil conflict.31 The consensus among scholars of mortality data in transition countries has been that aggregate rates of all-cause adult mortality are sufficiently valid and reliable to permit comparative studies.6 32-36

We measure rapid economic transition policies in two ways: first, using a dummy variable for whether a country implemented a mass privatization program, as defined previously (0 prior to mass privatization, 1 thereafter); and second, by using EBRD privatization indices of progress in privatization (ranging from 1 – “planned” to 4.3 – “advanced market economy”) (Table 2).37

An issue with the EBRD privatization indices is that the main policy advisors at the EBRD backing the shock therapists were also those responsible for scoring progress in privatization. Since coding occurred after country performance had been observed, there might be ideological pressure to code more successful countries as being more radical reformers. According to the EBRD, the privatization codings “reflect the judgment of the EBRD’s Office of the Chief Economist about country-specific progress in transition.”37

Our measure of mass privatization program implementation overcomes the observer biases and subjectivity in the EBRD indices. The EBRD Transition Report Series describes when countries implemented privatization program, how many firms were privatized under them, and by what method this privatization was accomplished.38 We use this data to code a large jump as a 25% transfer, which corresponds to a jump from one to three on the EBRD large-scale privatization index scale. Since the correlations between the EBRD large-scale index and small-scale index are statistically indistinguishable by our analysis (r=0.97 in Russia, for example), we proceed using an average of the large- and small-scale indices to reduce measurement errors.


We adjust for Log GDP per capita to control for income level , which is strong and robust determinant of health. [[In the long run. Short term movements at population level are often in opposite directions eg ref above Gerdtham ]] We also control for political changes with a widely used index of democratization from Freedom House because, given the known [[??]] association between democracy

[[You should be more specific about the index used. Is it the index for ‘Political rights’? if so say so. I would agree that this is a reasonably good proxy for democracy. The civil liberties index will be more weakly associated with democracy at a global level eg Singapore, Hong Kong, Brunei. Whether or not ‘democracy’ associates strongly with health levels depends very much on what else is in the model. If one uses the World Bank’s governance indicators and distinguish democracy (‘voice and accountability’) from civil liberty and state effectiveness in fairly inclusive datasets then state effectiveness soaks up most of the variance – as anyone reflecting on recent global mortality trends might suspect: eg the outstanding performance of well governed non-democratic countries such as Singapore, Hong Kong, Brunei, Oman etc. For a view contrary to yours on democracy and health see: Horton R. REFLECTING ON HEALTH CHALLENGES: Remarks for the Official Launch of WHO's Commission on Social Determinants of Health. http://www.who.int/social_determinants/speech/en/print.html.

There is also perhaps an inconsistency between favouring an emphasis on the quality of institutions to account for the course and effects on well being of economic transformations and ignoring the qualitative performance of state institutions in the political sphere. ]]

and life expectancy39 these changes might confound the relationship between the economic changes and health. To isolate the effect of privatization we control for price and trade liberalization, the main complementary policies recommended by the shock therapists. War affects reporting of mortality, so we use a dummy for the occurrence of military or ethnic conflict. The population dependency ratio, which measures the ratio of total working-age adults to elderly and infants, controls for the proportional size of the workforce and the relative cost of state social welfare systems. We also control for demographic characteristics using urbanization ratios and population tertiary education rates.

As we are interested primarily in fluctuations in mortality, our regression models also use a set of country dummy variables to net out relatively fixed aspects of national surveillance infrastructure, initial country conditions and predispositions to higher mortality [I presume these are country specific slopes … is that correct? It might help the less numerate (like me) to make sense of it if it was described this way]]. In effect, this makes the data more comparable. Country dummy variables also effectively hold constant possibly confounding geographic effects such as proximity to Western Europe or membership of the former Soviet Union as well as some of the potential coding bias in the World Bank privatization indices.

Thus our model is

AMRit = α + βPRIVit + βGDPit + βLIBit + βTRADEit + βDEMit + βWARit + βDEPit + βEDUCit + μi +εit

Here i is country and t is year, AMR is logged adult male mortality rates (working ages of 15 to 59), PRIV is one of the two privatization measures, GDP is log GDP per capita in constant US dollars, LIB is the EBRD price liberalization index, Trade is the EBRD foreign exchange and trade liberalization index, DEM is the democratization index, WAR is a dummy for military conflict, EDUC is the percentage of population with tertiary education, URBAN is the percentage of the population living in urban settings, DEP is the population dependency ratio, μ is a set of country fixed effects, and ε is the error term.

Results

Effect of Mass Privatization on Male Working Age Mortality Rates

Table 3 shows the results of our basic model. Mass privatization programs are associated, on average, with a 12.3% increasein adult male mortality (p<0.001). Compared with the 25.8% increase in the worst performing countries at the peak of the mortality crisis in 1994, this is a substantial association. In our dataset, mass privatization can on average account for roughly half of the mortality rate increases in the worst performing countries and a large fraction of the differences in the mortality rate increases between countries. To further put this effect in perspective, the estimated effect of increasing the rate of economic growth ten-fold would not be enough to offset the increase in mortality rates resulting from mass privatization (β Log GDP per capita = -0.11, p<0.001, not shown). Clearly, even if mass privatization might enhance economic growth, the effect would not be anywhere near this magnitude.


The EBRD privatization index also increases adult mortality rates (4.10%, 95% CI: 1.78% to 6.41%). While our controls hold constant membership of the former Soviet Union, they do not preclude interactions between being in the former Soviet Union and the effects of privatization. If the pace of privatization mattered more than the level of privatization, then the EBRD index should have a greater effect in countries where mass privatization as a transition strategy was more dominant.

This is exactly what we found. When we restrict the sample to Former Soviet Union countries such that changes in the EBRD index more accurately reflect the implementation of mass privatization, variations in the EBRD privatization index are even greater determinants of adult mortality. Each one unit increase, roughly the same as one standard deviation, increases mortality by 10.3%. Since the average change in the privatization index over the entire period was around two units, this amounts to roughly the same effect size as that attributed to our measure of mass privatization implementation and the net effects of the two become statistically indistinguishable.

Do these results offer an explanation of differences in mortality changes in the former Soviet Union? Figure 2 compares the trajectories of Russia, which implemented mass privatization in 1992, with its neighbour Belarus, which adopted a more gradual approach to transition. By 1994, at the peak of Russia’s mortality crisis, Russia had privatized over 112,000 firms or more than half of all Russian state-owned enterprises, while over this same period Belarus only privatized 640 firms, or less than 10% of their state-owned sector. Unemployment rates in both countries started at very similar low levels, but in Russia they increased over 13-times as much as in Belarus; in parallel, mortality rates in Russia increased four times as much as in Belarus (roughly a 11.3% difference in the average mortality rate increase). Our estimate using the EBRD index of a 20.6% increase in mortality rates attributable to privatization in Russia (2 point increase) to a 8.8% estimated for Belarus (0.85 point increase), closely matches the cumulative mortality differences over time between these countries. Similarly, our measure of a mass privatization program estimates a 18.4% increase in adult male mortality rates associated with this policy: this is strikingly close to the observed 17.8% average increase in Russia between 1992 and 1994.


Effect of Mass Privatization on Unemployment Rates

We now attempt to bridge the cross-national privatization results and the public health findings by testing privatization’s relationship to unemployment. Privatization has significant and pronounced effects: implementing mass privatization increases unemployment by 69% compared to countries where the process was more gradual. In the full country sample the effect of a one unit increase in the EBRD index was 46% and for the former Soviet Union sample the effect was again larger at 68%. This reiterates that rapid mass privatization caused more job losses than slower privatization, most likely because it provided fewer opportunities for firms to adapt and stay financially solvent.

A major caveat in using the International Labor Office unemployment data is that they reflect registered unemployment levels which are much lower than actual unemployment levels. Despite this limitation, the results provides evidence of the mechanism by which privatization effected increased mortality. The models also net out much of the bias by evaluating changes within countries over time. It is also difficult to imagine how variations in the propensity to register for unemployment alone could account for these trends. To the extent they might, it runs against our hypothesis: areas with the most privatization had the least adequate social safety nets because privatization, by design, critically hampered the state’s revenue base. This means that in countries where more privatization occurred people would have had less incentive to register for unemployment, so any residual bias renders our estimates extremely conservative.

Interaction between Social Capital and Rapid Privatization

If dislocation serves as a key mechanism linking rapid privatization to increased mortality rates, then it might be expected that rapid privatization’s adverse effects would be in part mitigated in countries which had more inclusive social policies or higher levels of social cohesion. Figure 3 shows the results of a regression model which interacts mass privatization implementation with the percentage of a country’s population who are members of at least one social organizations (such as a labour union, church or religious group, sports club or a political organization) for 18 countries taken from the European World Values Survey (EWVS).40


This shows how the effect of rapid mass privatization on adult mortality rates linearly decreases with increasing social capital. In fact, in countries where more than 45% of the population was a member of a social organization, mass privatization had no significant adverse effect. Since social capital does not change greatly over time, this measure is almost surely acting as an effect modifier rather than a confounder in our models. This finding may help to explain why mass privatization programs in the Czech Republic, which had the second highest social membership (48%, equal to Western Europe’s average level) of all the former communist countries, had no significant negative effect, but in the former Soviet countries, where social membership was much lower (~10%), rapid privatization had extremely adverse consequences. Other measures of social capital from the EWVS such as trust produce similar results (not shown).

Robustness Checks

We have performed a series of robustness checks. First we removed the complementary transition policies, including price liberalization and trade liberalization, and also added period dummies and indicators for stabilization programs. None of the mortality results was significantly affected. Since most mass privatization programs were implemented in the span of two years, we replicated our models using a coding of 0 prior to, 1 during, and 0 after mass privatization: the results were statistically indistinguishable. We also checked our coding with the World Bank economists in charge of mass privatization implementation, who agreed with all of our classifications except for Romania, which they considered an indeterminate case. We re-coded Romania as a non-mass privatizer and found that the overall results were unchanged. We also sequentially removed countries where data are suspected to be misreported, such as the Central Asian and war-torn countries. The results remained consistent and were slightly larger (as found with the former Soviet Union sample). Using alternative estimation procedures, such as first-differences or more advanced methods for adjusting for serial correlation also do not affect our findings. A complementary paper has examined the relationship between privatization and specific causes of death, finding specific associations that are consistent with the known effects of economic transition on health and, in particular, the major role played by alcohol as an immediate cause of rapid changes in mortality.4,5

Discussion

In writing about Stalin’s policies, John Maynard Keynes notes that

“We have a fearful example in Russia today of the evils of insane and unnecessary haste. The sacrifices and losses of transition will be vastly greater if the pace is forced…”76

Today we can witness the same process but in reverse: the new regimes did not call for radical statism but rather for radical privatization to create capitalism.

As Emile Durkheim reminds us,77 any disruption to the established social order creates high levels of anomie, or social stress. Mass privatization is a case-in-point: by rapidly transforming existing enterprises into private property in the absence of a real class of strategic owners, many firms went bankrupt and excess jobs were lost. People were left disoriented without jobs amidst unfamiliar market conditions. While this period was predicted by the shock therapists, who viewed it simply as a period of “resource reallocation”, it had real human costs: even if capital resources could be reconfigured rapidly, people simply are not able do so as quickly. Inclusive social structures during this period appear to have been critically important in counter-balancing the harms of this dislocation, enabling people to cope with social disruptions, a finding consistent with research on the determinants of health at an individual level.78

Our findings are consistent with a considerable body of research on mortality in the post-communist period, which has provided evidence for the role of a number of factors including acute psychosocial stress 6 41-45 46 47 48, abridged access to and declining quality of medical care (much provided at workplaces) 49 50 51 52 53, impoverishment53-55, rapid pace of transition52, increased unemployment 56 57 58, rising social inequalities59 60, social disorganization61, worsened corruption62, and the erosion of social capital 59 63. Although it would be too simple to attribute a direct cause and effect relationship, each of these findings can be linked, in some way, to mass privatization programs.64-75

Did going more slowly hurt the prospects for capitalism? Is Slovenia – one of the more gradual privatizers – any less capitalist than Ukraine? In fact, by approaching transformation rapidly and radically, it appears that prospects for Western-style capitalism may have been seriously impaired in countries like Russia. Slower privatizers manage to reach a capitalist endpoint but did not absorb nearly the same amount of social costs along the road (Table 1).

The policy implications are clear. Great caution should be taken when macro-economic policies seek to radically overhaul the economy without considering potential effects on the population’s health.

[[living conditions. As variants of shock therapy are still discussed for China [[I would remove this reference – see Popov on China and Vietnam ie if Vietnam could cope with shock therapy why couldn’t China? … but in any case there has already been massive ‘quasi-privatisation’.]] , India, Egypt and numerous other developing and middle-income countries – including Iraq – which are just beginning to privatize their large state-owned sectors, the lessons from the transitions from communism should be kept in mind.]]

Figures and Tables



Figure 3. Interaction between Mass Privatization and Social Capital

Table 1. Change in Total Adult Male Mortality Rates and Amount of Privatization, Postcommunist Countries from 1991 to 1994






Note: Results presented from the regression model AMRit = α + β1PRIVit + [β2SCi ] + β3PRIVit*SCi + βX + μi +εit. using the estimation sample of countries for which social capital data are available (Number of countries = 18). [∙] denote that the time-invariant social capital term is captured by the country-specific effect, μi; SC is a measure of social capital taken from the European World Values Survey. β1PRIVit = 0.129019 and β3PRIVit*SCi = -0.001898. Clustered standard errors calculated from the robust variance-covariance matrix using the formula √var(β1)+XSCvar(β3)+2XSCcov(β1β3).

Table 1. Change in Total Adult Male Mortality Rates and Amount

of Privatization, Postcommunist Countries from 1991 to 1994

Measure 1991-1994

Best Five Countries Albania, Croatia, Czech

Republic, Poland, Slovenia


Mortality Rates -6.7%

Change in EBRD


Index

1.1

Change in Male


Worst Five Countries Kazakhstan, Kyrgyz

Republic, Latvia, Russia,

Tajikistan


Mortality Rates 25.8%

Change in EBRD


Index

1.6

Change in Male


Note: Geometric means calculated for average percentage changes. Adult mortality rates [[SPECIFY EXACT MEASURE]] are from the UNICEF Monitoring Transition in Central & Eastern Europe Database. Enterprise Bank for Reconstruction and Development (EBRD) average privatization index ranges from 1 – communist to 4.3 – complete market. Unemployment rates are registered unemployment rates from the International Labor Organization, and are presented for 1992 to 1994 due to missing comparative data for 1991.


MEASURE OF

PRIVATIZATION DESCRIPTION OF CODING


0 Country did not implement a program that transferred the ownership of at least

25% of large-state owned enterprises to the private sector through vouchers and

give-aways to firm insiders.

1 Country implemented a program that transferred the ownership of at least 25%

of large-state owned enterprises to the private sector through vouchers and give-

aways to firm insiders.

EBRD Small-Scale



1 Little progress




4+ Standards and performance typical of advanced industrial economies: no state

ownership of small enterprises; effective tradability of land

EBRD Large-Scale





3 More than 25 per cent of large-scale enterprise assets in private hands or in the

process of being privatized (with the process having reached a stage at which the

state has effectively ceded its ownership rights), but possibly with major

unresolved issues regarding corporate governance.

4 More than 50 per cent of state-owned enterprise and farm assets in private

ownership and significant progress on corporate governance of these enterprises.

4+ Standards and performance typical of advanced industrial economies: more than

75 per cent of enterprise assets in private ownership with effective corporate

governance

Note: Mean scores presented for 25 transition countries. † - Variable definitions were originally developed in 1994 but were refined and amended in later reports; Presented definition are quoted directly from the EBRD 1999 Transition Report. “Transition indicator scores reflect the judgment of the EBRD’s Office of the Chief Economist about country-specific progress in transition” (EBRD 2007).



Effect on Male Mortality Rates

Ages 15 to 59

All countries Former Soviet

Union


Privatization

12.3%*

(8.6% to 16.0%)

18.4%*

(12.4% to 24.5%)


unit of average EBRD

privatization

4.1%*

(1.8% to 6.4%)

10.4%*

(6.7% to 14.1%)

Note: Coefficients calculated as semi-elasticities presented; Robust standard errors in parentheses. Models also control for Log GDP per capita, EBRD price liberalization index, EBRD trade liberalization index, democratization, population dependency, the percentage of population living in urban settings, the population education level, and country-specific fixed effects. Number country-years for all countries is 289, number of countries is 24. Number of country-years for the former Soviet Union is 177, number of countries is 15.

Significance at * p<0.001



Effect on Male Unemployment

Rates

All Countries Former Soviet

Union


Privatization

69%*

(43% to 94%)

76%*

(44% to 107%)


unit of EBRD average

privatization

46%*

(31% to 61%)

68%*

(38% to 98%)

Note: Coefficients calculated as semi-elasticities presented; Robust standard errors in parentheses. Models also control for Log GDP per capita, EBRD price liberalization index, EBRD trade liberalization index, democratization, education rate, population dependency, the percentage of population living in urban settings, the population education level, and country-specific fixed effects.

Significance at * p-<0.001

Authors Contributions

DS compiled the data, conducted the empirical analysis and drafted the manuscript; MM oversaw the design of the study, facilitated the interpretation of the findings, and helped draft the manuscript; LK originally conceived of the study, provided background information on the Post-communist context, and guided the overall direction of the analysis.

Funding

MM’s work in transition countries is supported by the European Observatory on Health Systems and Policies and the Wellcome Trust.

Acknowledgement

The authors would like to thank Erica Richardson for assistance on, and comments and criticisms of, various drafts of this paper.

Conflict of Interest Statement

None declared

DS had full access to all the data in the study and final responsibility for the decision to submit for publication.

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Mass

Privatization

begins

Total of 112,625

State-owned

Enterprises

Privatized (over

50%)

Privatization

reversal

(re-nationalization)

’98 Russian Financial

Crisis

(Per Capita GDP

drops 30%)




http://www.who.int/social_determinants/speech/en/print.html




http://www.who.int/social_determinants/speech/en/print.html

Table 2. Effect of Privatization on Male Life Expectancy in

Transition Countries, 1991-2002

Covariates (1) (2) (3)

Mass Privatization -1.58

(0.23)*** – –

EBRD Average

Privatization Index –

-0.49

(0.18)** –

EBRD Cumulative

Privatization Index – –

-0.03

(0.03)

Log(GDP per capita) 1.61

(0.30)***

1.81

(0.30)***

1.79

(0.35)***

EBRD Price

Liberalization Index

-0.22

(0.15)

-0.26

(0.14)

-0.28

(0.15)

Heritage Foundation

Democracy Index

0.24

(0.05)***

0.25

(0.06)***

0.22

(0.06)***

Military Conflict -0.74

(0.29)**

-0.64

(0.30)*

-0.63

(0.31)*

Percentage of

Population Urban

-0.63

(0.14)***

-0.45

(0.13)***

-0.39

(0.14)**

Population

Dependency Ratio

-0.08

(0.08)

-0.15

(0.06)

-0.16

(0.07)*

Percentage of

Population with

Tertiary Education

-0.01

(0.01)

-0.02

(0.02)

-0.01

(0.02)

Table 3. Effects of Mass Privatization and Log GDP per Capita on Log Male Death Rates

in 25 Transition Countries by Age, 1991-2002

Covariates Infanta Under-5

a 5-14 15-59 60+

Mass Privatization 2.92%*

(1.44)

2.00%

(1.49)

0.20%

(0.95)

13.51%***

(2.31)

1.32%***

(0.38)

Log GDP per

capita

-0.10%***

(0.01)

-0.11%***

(0.01)

-0.05%***

(0.01)

-0.14%***

(0.03)

-0.02%**

(0.01)

Denialism at The Economist

PRIVATISATION AND MORTALITY: CRITIQUES

• Gerry, C. 2012 “Re-visiting the mass privatisation-mortality debate: A response to Stuckler, King and McKee”. Social Science & Medicine 75: 32-5

• Gerry, C. 2012. “The journals are full of great studies, but can we believe the statistics? Revisiting the mass privatisation and mortality debate”. Social Science & Medicine, 75(1): 14-22.

• Gentile, M. 2012. “Debate: Mass Privatisation, Unemployment and Mortality”. Europe-Asia Studies 43(4): 785-7.

• Earle, J. and S. Gehlbach. 2011. “Did Post-communist Privatization Increase Mortality?”. Comparative Economic Studies 53: 239–60.

• Earle, J. and S. Gehlbach. 2010. “Correspondence on Stuckler, King and McKee’s ‘’Mass Privatization and the Post-Communist Mortality Crisis: A Cross-National Analysis’’’. The Lancet 375(9712): 372-4.

• Earle, J. 2009. “Mass Privatization and Mortality”. The Lancet 373(9671): 1247.

• Gerry, C., T. Mickiewicz, and Z. Nikoloski. 2009. “Did mass privatization really increase post-communist mortality?”. The Lancet 375(9712): 371.

PRIVATISATION AND MORTALITY: RESPONSES

• Stuckler,D., L. King and M. McKee. 2012. “The disappearing health effects of rapid privatization: a case of statistical obscurantism?” Social Science and Medicine 75(1): 23-31.

• Stuckler, D., L. King and M. McKee. 2012. “Debate: Response to Michael Gentile ‘Mass Privatisation, Unemployment and Mortality’”. Europe-Asia Studies 64(5): 949–53.

• Stuckler, D., L. King and M. McKee. 2010. “Reply to Earle and Gerry” (with David Stuckler and Martin McKee). The Lancet 375(9712): 372-4.

• Stuckler, D., L. King and M. McKee. 2009. “Mass privatisation and mortality — Authors' reply”. The Lancet 373(9671): 1247-8.

• Stuckler, D., L. King and M. McKee. 2009. “How to make a mortality crisis disappear: statistical manipulation”. The Lancet 373(9671). Web appendix. Pp.1-33.

PrivMort

• Multi-disciplinary project in the subfield of the Political Economy of Public Health

• Russia, Belarus and Hungary

• Funded by the ERC – 3,5 million EUR

• About 300,000 respondents and relatives in total

• PI: Lawrence King

• Senior investigators: Ivan Szelenyi, Michael Marmot, Vladimir Popov, Martin Bobak, Mike Murphy, Martin McKee, Irina Kolesnikova

• Research Team: Darja Irdam, Mihaly Fazekas, Gábor Scheiring, Katarzyna Doniec, Aytalina Azarova, Alexi Gugushvili

Main Objectives

1) to test the theory on the link between privatization and mortality

2) to understand whether the post-Soviet mortality in general and the privatization-induced mortality in particular are moderated by class and occupational position

3) to examine the effect of class, life-style habits and community factors on health outcomes of the post-Soviet transitions

PrivMort Data

I - Settlement-level

• Economic characteristics of the settlement

• Privatization processes

• Mortality

• Other socio-economic indicators

PrivMort Data

II – Individual-level – Respondents

• Non-fatal outcomes of transitions

• Education

• Labor market situation

• Religion and other social indicators

• Economic welfare

• Self-reported health behaviour

PrivMort Data

II – Individual-level – Relatives

• Similar, but more detailed socio-economic characteristics

• Migration

• Mortality and morbidity

Preliminary results of settlement-level analysis in Russia

• The European part of the country

• Settlements with 10,000-100,000 inhabitants

• Data available for 536 towns from 1990 to 2010 (various official sources)

• Privatization variable – share of private ownership of main enterprise in mono-industrial towns (the average of the main enterprises in multi-industrial towns)

• Statistical method – Various specification of fixed-effects models (selection is based on Robust Hausman test)

Crude death rate (per 1,000 people)

5,0

7,0

9,0

11,0

13,0

15,0

17,0

19,0

21,0

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

Selected towns Russia overall

Share of privatized enterprises in the selected towns

0,0

10,0

20,0

30,0

40,0

50,0

60,0

70,0

80,0

90,0

100,0

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

Crude death rate (per 1,000 people). Pooled time-series fixed- and random-effects models with continuous

privatization variable M1:FE M2:FE M3:FE M4:FE M5:FE M6:FE M7:FE M8:FE M9:FE M10:RE

Share of privatized enterprises

(0-100%)

0.03*** 0.02*** 0.03*** 0.03*** 0.02*** 0.02*** 0.03*** 0.03*** 0.02*** 0.01***

Mono-industrial towns –0.48

Privatized * mono towns 0.00**

Industry output in constant prices

(1991)

–0.00*** –0.00** –0.00***

Share of lose-making

enterprises(0-100%)

0.01 –0.01 –0.00*

CPI (in comparison to 1991) –0.00*** 0.00*** 0.00**

Employees in industry (per 10,000) 0.00*** 0.00* 0.00

Unemployment rate (current) –0.00 –0.02*** –0.02***

Number of physicians (per 10,000) 0.00 0.00 –0.02***

Number of nurses (per 10,000) 0.00 0.00*** 0.00

Hospital beds (per 10,000) –0.00** –0.01*** 0.01***

Alcohol consumption 0.51*** 0.46*** 0.38***

Alcohol prices –0.00*** –0.00*** –0.00***

Old-age dependency ratio 0.02*** 0.02*** 0.02***

Number of birth (per 10,000) –0.09 –0.02 –0.18***

Number of divorces (per 10,000) 0.10*** 0.15* 0.11***

Number of libraries (per 10,000) –0.11*** –0.10* –0.04

Number of cultural institutions (per

10,000)

–0.02 0.01 0.04

Net migration (per 1,000) 0.01 –0.00 0.01

Pollutants, ‘000 tones (per 10,000) –0.00** 0.00 0.00

R-Squared

Within 0.25 0.25 0.23 0.24 0.33 0.34 0.24 0.25 0.35 0.33

Between 0.04 0.09 0.04 0.03 0.03 0.16 0.02 0.04 0.01 0.24

Overall 0.11 0.13 0.09 0.08 0.13 0.18 0.09 0.10 0.08 0.23

Number of observations 5,250 3,796 4,750 4,985 5,213 4,635 5,056 4,869 2,806 2,806

Number of towns 532 523 525 529 532 505 528 522 468 468

***, **, and * significant at 0.01, 0.05, and 0.10 levels.

Crude death rate (per 1,000 people). Pooled time-series fixed-effects models with a dummy variable of towns with

50% or more privatization M1:FE M2:FE M3:FE M4:FE M5:FE M6:FE M7:FE M8:FE M9:FE

50% enterprises or more in

private ownership

2.30*** 1.73*** 2.11*** 2.17*** 1.61*** 1.38*** 2.17*** 2.26*** 0.82***

Industry output in constant prices

(1991)

–0.00*** –0.00**

Share of lose-making enterprises(0-

100%)

0.01 –0.01

CPI (in comparison to 1991) –0.00*** 0.00***

Employees in industry (per 10,000) 0.00 0.00

Unemployment rate (current) 0.00 –0.02***

Number of physicians (per 10,000) 0.00 0.00

Number of nurses (per 10,000) 0.00 0.00

Hospital beds (per 10,000) –0.00*** –0.01***

Alcohol consumption 0.56*** 0.50***

Alcohol prices –0.00*** –0.00***

Old-age dependency ratio 0.02*** 0.02***

Number of birth (per 10,000) –0.16*** –0.07*

Number of divorces (per 10,000) 0.10*** 0.15***

Number of libraries (per 10,000) –0.14*** –0.11**

Number of cultural institutions (per

10,000)

–0.02 0.01

Net migration (per 1,000) 0.00 –0.00

Pollutants, ‘000 tones (per 10,000) –0.00** 0.00

R-Squared

Within 0.25 0.25 0.23 0.24 0.33 0.34 0.24 0.25 0.35

Between 0.04 0.09 0.04 0.03 0.03 0.16 0.02 0.04 0.01

Overall 0.11 0.13 0.09 0.08 0.13 0.18 0.09 0.10 0.08

Number of observations 5,250 3,796 4,750 4,985 5,213 4,635 5,056 4,869 2,806

Number of towns 532 523 525 529 532 505 528 522 468


Further robustness checks. Crude death rate (per 1,000 people). Pooled time-series fixed-effects models

Following Gerry (2012) and Earle and Scott’s (2011) criticism, we also include in the regressions lagged privatization variable and country-specific time trend. M1:FE M2:FE M3:FE M4:FE M5:FE M6:FE M7:FE M8:FE M9:FE

1st specification

1 year lagged privatization 0.02*** 0.02*** 0.02*** 0.01*** 0.01*** 0.01*** 0.01*** 0.01*** 0.01***

Controls variables Yes Yes Yes Yes Yes Yes Yes Yes Yes

2nd specification

Current privatization 0.02*** 0.01*** 0.01*** 0.01*** 0.01*** 0.01*** 0.01*** 0.01*** 0.01***

1 year lagged privatization 0.01*** 0.01*** 0.01*** 0.01*** 0.00** 0.00*** 0.01*** 0.01*** 0.00***


3rd specification


Time trend 0.38*** 0.34*** 0.25*** 0.25*** 0.18*** 0.25*** 0.25*** 0.27*** 0.28***


4th specification


1 year lagged privatization -0.01*** 0.00 -0.00 -0.00 -0.00* -0.00 -0.00 -0.00 -0.00

Time trend 0.37*** 0.29*** 0.18*** 0.20*** 0.12*** 0.22*** 0.18*** 0.20*** 0.27***


5th specification


Time trend 0.14*** 0.14*** 0.13*** 0.15*** 0.05*** 0.17*** 0.14*** 0.14*** 0.15***

1 year lagged death rates 0.34*** 0.47*** 0.34*** 0.33*** 0.38*** 0.32*** 0.34*** 0.37*** 0.42***



Research Horizons

Propensity Score Matching in Russia

30 towns in total:

• 15 monotowns with mass privatisation

• 10 monotowns with gradual privatisation

• 5 multitowns with both fast and slow privatisation

Propensity Score Matching in Russia

Matching done based on:

• Crude death rates per 1000 population in 1991

• Pre-reform population

• Dependency ratio in 1991

• Average wage in US dollars in 1992

• Number of physicians per 10,000 population in 1991

• Floor area per person in 1991

• Death rates from alcohol poisoning per 100,000 population in 1991

• Emission of pollutants into atmosphere from stationary sources, total, thousand tons in 1991

Differences in average values for PSM covariates in Treatment and Control groups: Mass vs Gradual Privatization

Feedback is more than welcome

• Alexi Gugushvili [email protected]

• Larry King [email protected]



Table 1. Descriptions of Rapid Structural Privatization Variables from the Enterprise Bank for Reconstruction and Development

Mean Score Measure of

Privatization

Description of Coding

1991 2002


0 Country did not implement a program that transferred the ownership of at least 25% of

large-state owned enterprises to the private sector through vouchers and give-aways to firm

insiders.

1 Country implemented a program that transferred the ownership of at least 25% of large-state

owned enterprises to the private sector through vouchers and give-aways to firm insiders.

0 0.44

EBRD Small-Scale



1 Little progress




4+ Standards and performance typical of advanced industrial economies: no state ownership of

small enterprises; effective tradability of land

1.41 3.84

EBRD Large-Scale





3 More than 25 per cent of large-scale enterprise assets in private hands or in the process of

being privatized (with the process having reached a stage at which the state has effectively

ceded its ownership rights), but possibly with major unresolved issues regarding corporate

governance.

4 More than 50 per cent of state-owned enterprise and farm assets in private ownership and

significant progress on corporate governance of these enterprises.

4+ Standards and performance typical of advanced industrial economies: more than 75 per cent

of enterprise assets in private ownership with effective corporate governance

1.12 3.05

Note: Mean scores presented for 25 transition countries. † - Variable definitions were originally developed in 1994 but were refined and

amended in later reports; Presented definition are quoted directly from the EBRD 1999 Transition Report. “Transition indicator scores

reflect the judgment of the EBRD’s Office of the Chief Economist about country-specific progress in transition” (EBRD 2007).

Web Annex A2. Effects of Mass Privatization and Log GDP per Capita on Pathways of Population Health Impacts

Note: Robust panel-corrected standard errors in parentheses. Results presented from seven separate regression models. Two-way fixed effects models, using Prais-

Winsten transformation to adjust for country-specific serial correlation, control for the effects of EBRD price liberalization index, occurrence of military conflict,

percentage of population urban, age-dependency ratio, and percentage population with tertiary education.

* = p<0.05, ** = p<0.01, *** = p<0.001 (two-tailed tests).

Determinant

Alcohol

Consumption

(Liters per Capita)

Log Male

Alcohol Death

Rates

Log Male

Heart Disease

Death Rates

Log Male

Suicide Rates

Homicide

Rates

Log Male

Unemployment

Rates

Log Crime

Rates

Mass Privatization 0.81

(0.24)***

14.64%

(4.21)**

5.98%

(1.85)***

16.86%

(4.51)***

5.60

(1.85)**

44.83%

(13.62)***

4.19%

(4.13)

Log GDP per Capita -0.04

(0.30)

-0.11%

(0.06)

-0.10%

(0.02)***

0.04%

(0.08)

-0.88

(2.45)

-0.66%

(0.15)***

-0.23%

(0.05)***

Sources: World Development Indicators 2005 and EBRD 1992 and 1996 Transition Reports. ω

– when available, otherwise longest difference available; 1 – includes data from all periods,

equivalent to the unadjusted estimate of life expectancy (LE) on mass privatization;

Correlation coefficients: RLE=-0.29, RLEmale=-0.33, RLEfemale=-0.20.


Table 2. Mass Privatization and Life Expectancy by Country and Region

Region Country Mass

Privatization

Year Life Expectancy

Change (1989-2002)ω

Balkans Georgia Yes 1995 1.04 / 1.43%

Armenia Yes 1994 2.81 / 3.89%

Azerbaijan No - -5.11 / -7.35%

Baltics Lithuania Yes 1993 1.29 / 1.83%

Estonia No - 1.71 / 2.46%

Latvia Yes 1994 1.53 / 2.21%

Central Asia Kyrgyz

Republic

Yes 1994 -3.52 / -5.14%

Uzbekistan No - -2.50 / -3.61%

Kazakhstan Yes 1994 -6.66 / -9.79%

Turkmenistan No - -1.25 / -1.90%

Tajikistan No - -3.99 / -5.68%

Central Eastern

European

Czech

Republic

Yes 1994 3.50 / 4.88%

Slovenia No - 0.94 / 3.73%

Slovakia No - 2.73 / 1.30%

Poland No - 3.55 / 5.00%

Hungary No - 3.09 / 4.44%

Former Soviet Union Russia Yes 1992 -3.57 / -5.16%

Ukraine Yes 1995 -0.59 / -0.86%

Belarus No - -2.20 / -3.13%

SEE Romania Yes 1995 0.56 / 0.80%

Bulgaria No - 0.31 / 0.44%

Bosnia No - 0.96 / 1.31%

Macedonia No - 1.60 / 2.22%

Croatia No - 1.80 / 2.50%

Albania No - 1.85 / 2.56%

Moldova Yes 1994 -0.55 / -0.81%

Total ∆ Avg. ∆ Privatization -0.38 / -0.61%

Avg. ∆ Non-Privatization +0.23 / 0.36%

Difference of Avg. LE ∆ Privatization – ∆NonPrivatization -0.61 / -0.97%

Average LE Difference1 Avg LE Privatization – Avg LE

NonPrivatization -0.90

Mass Privatization and % GDP per capita Growth 1989-2003

Variable Model 5 Model 6 Model 7 Model 8

Mass privatization -0.446** -0.36** -0.368** -0.361**

(0.118) (0.123) (0.123) (0.112)

Initial GDP per capita (log) – 0.107 0.08 0.036

(0.109) (0.123) (0.115)

Initial population (log) – -0.057 -0.048 -0.049

(0.048) (0.045) (0.053)

Presence of oil – -0.007 0.014 0.033

(0.096) (0.1) (0.097)

Military conflict – -0.09 -0.089 -0.041

(0.208) (0.214) (0.212)

Transition progress – – 0.07 -0.038

(0.089) (0.135)

Central Eastern Europe and Baltics – – – 0.255

(0.204)

Constant 1.696*** 1.767 1.65 2.184

(0.083) (1.374) (1.37) (1.31)

Adj. R

2 0.412 0.384 0.346 0.366

N 24 24 24 24

Mass Privatization and EBRD Quality of Governance Index (1= worst, 3= best)

Covariates Coefficient

of Control

Coefficient of Mass

Privatization

Coefficient

of Control

Coefficient of EBRD

Avg. Privatization N

Economic and Policy (Q)

Foreign Direct Investment 0.02

(0.01)

-1.25

(0.23)***

0.03

(0.02)

-0.45

(0.14)** 302

EBRD Foreign Exchange &

Trade Liberalization

0.15

(0.11)

-1.43

(0.24)***

0.06

(0.11)

-0.47

(0.15)** 290

Hyperinflation -0.08

(0.16)

-1.29

(0.23)***

-0.01

(0.05)

-0.43

(0.15)** 302

Health System (Z)

Log Health Spending per

Capita

-0.09

(0.17)

-1.19

(0.25)***

-0.05

(0.16)

-0.42

(0.17)* 258

Health Spending as a

Percentage of Total

Government Spending

2.63

(2.05)

-1.23

(0.23)***

2.58

(1.94)

-0.37

(0.16)* 253

Number of Physicians per

1000 population

0.03

(0.21)

-1.28

(0.22)***

0.25

(0.23)

-0.42

(0.17)*** 281

Hospital Beds -0.03

(0.09)

-1.57

(0.21)***

0.00

(0.11)

-0.43

(0.20)* 274

Diet and Nutrition (N)

Protein Availability 0.08

(0.10)

-1.25

(0.23)***

0.10

(0.10)

-0.51

(0.16)*** 297

Log Fruit and Vegetable

Availability

0.36

(0.59)

-1.34

(0.23)***

0.53

(0.53)

-0.62

(0.20)** 281

Log Caloric Availability 0.13

(0.92)

-1.47

(0.23)***

-0.37

(0.93)

-0.54

(0.17)** 299

Control Variables

Table 7. Endogenous Determinants of Mass Privatization

Covariate Probit† Probit ME

† LPM LPM (FEM)

γ

log(GDP) 0.43 (0.28) 0.08 (0.06) 0.02 (0.02) -0.08 (0.07)

log(FDI) -0.35 (0.35) -0.65 (0.61) -0.16 (0.63) 0.02 (0.45)

log(IMF) 0.03 (0.02) 0.01 (0.00) 0.00 (0.00) 0.01 (0.00)**

Urbanization -0.04 (0.05) -0.01 (0.01) -0.00 (0.00)* -0.04 (0.02)

*

Dependency 0.09 (0.06) 0.02 (0.01) 0.01 (0.01) 0.03 (0.01)**

Fertility -3.46 (0.99)**

-0.65 (0.25)**

-0.23 (0.10)* -0.28 (0.08)

**

Education -0.11 (0.03)**

-0.02 (0.01)**

-0.01 (0.00)**

-0.01 (0.00)**

Political Freedom -0.35 (0.20) -0.07 (0.04) -0.04 (0.02) -0.08 (0.02)

*

Price Liberalization 1.44 (0.25)**

0.27 (0.10)**

0.16 (0.03)**

0.07 (0.03)*

Years Central Planning 0.04 (0.04) 0.01 (0.01) 0.00 (0.00) -

Ethnic Minority 1.48 (0.46)**

0.28 (0.13)**

0.23 (0.04)**

-

FSU 4.81 (1.10)**

0.79 (0.14)**

0.79 (0.11)**

-

CEEB 0.77 (0.86)* 0.17 (0.22) 0.09 (0.08) -

Number of

Observations

313 313 313 313

Number of Countries 26 26 26 26

χ2 196.83

** 196.83

** 184.85

** 511.47

**

Pseudo-R2 0.56 0.56 0.45 0.83

Note: † - clustered standard errors for intra-group correlation;

γ – Prais-Winsten transformation to

accommodate first-order autocorrelation; Discrete marginal effects given by ΔF/Δx = F(x1*β) - F(x0* β);

Continuous marginal effects evaluated at x ; * = p<0.05; ** = p <0.01 (two-tailed t-test).

Endogenous Selection Bias: Determinants of Mass Privatization

Table 9. Robustness Tests and Selection Models

Model Type Coefficient on

Mass Privatization

Coefficient on

log (GDP)

Coefficient on

λ

R2

POLS -1.79 (0.32)** -0.33 (0.11)** - 0.37

2SLS† -1.17 (0.43)** 0.08 (0.16) - 0.36

Treatment Effectsζ -3.34 (0.40)** -0.35 (0.11)** 1.55 (0.24)** 0.46

Random Effects†, ζ

-5.14 (0.53)** 0.37 (0.14)** 3.24 (0.33)** 0.62

Fixed Effects†,ζ

-0.91 (0.35)** 1.38 (0.24)** 0.04 (0.20) 0.94

Note: Models adjusted for EBRD price liberalization index, age-dependency ratio,

percentage of population urban, fertility rate, and percentage population with tertiary

education; † - Prais-Winsten transformation to accommodate AR(1) error structure;

ζ -

standard errors adjusted for selection; * = p<0.05; ** = p<0.01 (two-tailed tests)

Selection Models

Sources of data: Towns

• Database «Economy of Russian cities” provided by Main Interregional Center of the Processing and Dissemination of Statistical information Of the Federal State Statistics Service (GMC Rosstat). http://www.gmcgks.ru/

• Population of cities in Russia since 1897. Yaroslavl, 1986 (Historical data on the population and the creation of cities). Hard copy.

http://www.gmcgks.ru/

http://www.gmcgks.ru/

Sources of data: Companies

• Database provided by Centre for Economic and Financial Research (CEFIR) / Original source of the Federal State Statistics Service (Goskomstat) .

• Database Professional Market and Companies System (SPARK). The largest database of Russian, Ukrainian and Kazakh companies. The database contains official information from over 20 different sources, including federal departments, ministries and government agencies, key mass media and companies themselves. (http://www.spark-interfax.ru/Front/About.aspx?tabId=1 )

• Unified State Register of Enterprises and Organizations of the Russian Federation (EGRPO) Data on OKPO, the founders of legal entities. (http://www.egrpo.ru/

• Unified State Register of Legal Entities (EGRYuL). Information about full and abbreviated companies’ names in Russian and native regional languages, legal form, location, information on shareholders and the size of shares in authorized capital of the companies. Data from Federal Tax Service. http://egrul.nalog.ru/

http://www.spark-interfax.ru/Front/About.aspx?tabId=1



http://www.egrpo.ru/

http://egrul.nalog.ru/

Settlements Selection

• Hungary: all settlements 10,000-50,000 inhabitants

• Belarus: all monotowns; multi-towns with population larger than 10,000

• Russia: European part; settlements with 10,000-100,000 inhabitants

PrivMort Data

III - National Representative Survey in Russia

• 1,500 respondents

• Comparing the mortality data with the general average population

• Increases generalizability

Differences in average values for PSM covariates in Treatment and Control groups: Mono vs Multi Towns (Russia)

Descriptive Statistics

0,00 5,00 10,00 15,00 20,00 25,00 30,00

Heart attack

Accident

Homicide

Suicide

Cancer

Alcoholism,including alcohol poisoning

Other heart disease (i.e. not heart att

Stroke

Other cause (specify)

Cause of Death - men (%)

Belarus

Hungary

Russia


0 5 10 15 20 25 30 35 40

Heart attack

Accident

Homicide

Suicide

Cancer

Alcoholism

Other heart disease

Stroke

Other cause

Cause of Death - women (%)

Russia Hungary Belarus


0,00 10,00 20,00 30,00 40,00 50,00 60,00 70,00

Almost every day

Several times a week

About 2-4 times a mon

Up to once a month (o

Used to drink, but qu

Never drank

Binge Drinking - men (%)

Belarus

Hungary

Russia


0 10 20 30 40 50 60 70 80 90

Almost every day

Several times a week

About 2-4 times a month

Up to once a month

#Used to drink that much but quitted

Never

Binge Drinking - women (%)

Russia Hungary Belarus

Neoclassical Sociological Theory of Privatization

Mass Privatization destroys firms creating a vicious circle of firm and state failure resulting in “patrimonial capitalism”

Strategic ownership via competitive ownership after state-sponsored restructuring is the best way to privatize, creating “liberal capitalism”

“Postcommunist Economic Systems” (with Iván Szelényi) in Neil Smelser and

Richard Swedberg (eds) Handbook of Economic Sociology (second edition). Princeton: Princeton University Press. 2005. Pp. 206-232.

“Shock Privatization: The Effects of Rapid Large Scale Privatization on Enterprise Restructuring.” Politics and Society 2003 (March):3-34.

“The State Led Transition to Liberal Capitalism: Neoliberal, Organizational, World Systems, and Social Structural Explanations of Poland’s Economic Success” (with Aleksandra Sznajder) American Journal of Sociology November. 2006. Vol. 12, No.3: 751-801.

Research Horizons

• PrivMort provides an analytical and methodological model for linking micro-level data with meso-level indicators

• More research on the effect of individual health-behavior, adaptations and preferences on mortality outcomes is needed

This report was presented at the 5th LCSR International Annual Conference “Cultural and Economic Changes under Cross-national Perspective”.

November 16 – 20, 2015 – Higher School of Economics, Moscow, Russia.

http://lcsr.hse.ru/en/conf2015

Настоящий доклад был представлен на V ежегодной международной конференции ЛССИ «Культурные и экономические изменения в

сравнительной перспективе».

16-20 ноября 2015 года – НИУ ВШЭ, Москва, Россия.















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