determinants of productivity at firm- and...

Determinants of productivity at firm- andindustry-level

Fabrizio Pompei

Department of EconomicsUniversity of Perugia

Economics and Industrial Dynamics (2015/2016)(II Semester, 2016)

Pompei Determinants of productivity Academic Year 2015/2016 1 / 29

Contents of the Lecture*

1 Relationships between productivity and industrialdynamics

2 Defining and measuring productivity

3 Determinants of Productivity

4 Internal Determinants

5 External Determinants

*The materials for this lecture have been drawn by Syverson C. (2011) What determinesproductivity? , Journal of Economic Literature, 49, 6, pp. 326-365


Relationships between productivity and industrial dynamics

Heterogeneity in productivity performancesand firm survival

Higher productivity producers are more likely to survive than their lessefficient industry competitorsProductivity is quite literally a matter of survival for businesses: thiscould explain why some firms can stand and some others exit fromthe industriesA study on the US manufacturing sector found that the plant at the90th percentile of the productivity distribution makes almost twice asmuch output with the same measured inputs as the 10th percentileplantChang-Tai Hsieh and Peter J. Klenow (2009), for example, find evenlarger productivity differences in China and India, with average 90-10TFP ratios over 5:1Regressing a producer’s current Total Factor Productivity (TFP) onits one-year lagged TFP yields autoregressive coefficients on the orderof 0.6 to 0.8


Relationships between productivity and industrial dynamics

Importance of micro-level productivitygrowth

Economic Growth: studies on micro-level productivity growth helpexplain the sources and the role of reallocations of economic activitytoward higher productivity producers (both among existing plants andthrough entry and exit) in aggregate productivity growth.

Industrial organization is linking productivity levels to technology,demand, and market structure (i.e. competition, the size of sunkcosts)

Labor economists have explored the importance of workers’ humancapital; the productivity effects of incentive pay; managerial talentand practices; social connections among coworkers in explainingproductivity differences, Trade: Theoretical frameworks usingheterogeneous productivity firms like that of Melitz (2003) are nowthe dominant conceptual lenses through which economists view tradeimpacts.


Defining and measuring productivity

Productivity in Concept

Productivity is efficiency in production: how much output is obtainedfrom a given set of inputs.

Single-factor productivity measures reflect units of output producedper unit of a particular input: labor productivity is the most commonmeasure of this type

Single-factor productivity levels are affected by the intensity of use ofthe excluded inputs: two producers my have different labourproductivity levels even though they use the same technology (itdepends on different capital intensity driven by different factor prices).

Total Factor Productivity (TFP) has the advantage to beinvariant to the intensity of use of observable factor inputs

TFP differences reflect shifts in the isoquants of a productionfunction: variation in output produced from a fixed set of inputs.



Productivity in Concept (2)

Higher-TFP producers will produce greater amounts of output withthe same set of observable inputs than lower-TFP businesses

Factor price variation that causes different factor intensities does notaffect TFP because it induces shifts along isoquants rather than shiftsin isoquants

Yt = AtF (Kt , Lt ,Mt)

where Yt is output; Kt capital, Lt labour, Mt intermediate materialand At is the factor-neutral shifter

In this type of formulation At is either the TFP: it capturesvariations in output not explained by shifts in the observableinputs

In other words TFP is a residual: it is the variation in outputthat cannot be explained based on observable inputs



Measuring Productivity

Several measurement issues arise when constructing productivitymeasures from actual production data

Output Measure:normally measured as revenue. Problem emergeswhen prices reflect not only quality differences, but market power. Inthis case we are not capturing efficiency

Labour Measure: there is the choice of whether to use number ofemployees, employee-hours, or some quality-adjusted labor measure

Capital: there is the choice of whether to use simply the firm’s bookvalue or constructing the stock using observed investments and theperpetual inventory method

Gross Output vs Value Added: Should one use a gross outputproduction function and include intermediate inputs directly, or shouldintermediates simply be subtracted from output so as to deal with avalue-added production function?



Measuring Productivity (2)

How to aggregate the inputs in a TFP measure?

We must weight the individual inputs appropriately when constructinga single-dimensional input index.

When the production function is Cobb-Douglas we have

TFPt = At = Yt

Kαkt Lαl

t Mαmt

where αj , with j = k , l ,m, are the output elasticities

We can estimate the elasticities αj by estimating the productionfunction

Ln(Yt) = α0 + αkLn(Kt) + αlLn(Lt) + αmLn(Mt) + ωt

where the estimated TFP would be

T̂FPt = Ln(Yt) − αkLn(Kt) − αlLn(Lt) − αmLn(Mt) = α̂0 + ω̂t


Determinants of Productivity

Determinants of Productivity: An overview

There are internal and external drivers of productivityInternal determinants:

Managerial Practices

Higher-Quality Labour and Capital

Information Technologies and R&D

Learning by Doing and Product Innovation

External determinants:

Productivity spillovers

Competition and Regulation

Input Markets

Market Demand


Internal Determinants

Managerial Practices

Managers coordinate the application of labor, capital, and intermediate inputs.One might expect poor management to lead to low-efficiency productionoperation

Bloom and Van Reenen (2007; 2010) offer one of the most comprehensivestudies relating management practices to productivity

Survey includes nearly 6,000 firms in seventeen countries (among othersGermany, France, Italy, UK, US, China, India, and Brazil)

They performed an interview-based evaluation tool that defines and scores18 basic management practices from one (worst practice) to five (bestpractice)

These best practices can be grouped in three broad areas:

1 Monitoring: how well do companies track what goes on inside their firms and use this forcontinuous improvement

2 Target setting: do companies set the right targets, track the right outcomes, and takeappropriate action if the three are incongruent?

3 People: are companies promoting and rewarding employees based on ability and effort andsystematically trying to hire and keep their best employees?



Managerial Practices (2)

Bloom and Van Reenen (2007; 2010) find that higher scores inpractices mentioned above are strongly associated tohigher-productivity

Two factors are important predictors of the quality of managementpractice in a firm

1 More intense competition in the firm’s market, measured in severalways

2 Management practice scores are lower when the firm is family-ownedand primogeniture determined the current CEO’s succession (i.e., heis the eldest son of the firm’s founder)



Managerial Practices (3)

Other within-firm work has suggested that the human resourcescomponents of management can affect productivity

Lazear (2000), and Bandiera, Barankay, and Rasul (2007 and 2009)tie nonstandard human resource management practices likepay-for-performance schemes, work teams, cross-training, androutinized labor-management communication to productivitygrowth

These practices may be complements: while they may have onlymodest impact on productivity when implemented in isolation, theirtotal impact is larger than the sum of its parts when used inconjunction

Alexandre Mas (2008) shows in a vivid case study how poormanagement-labor relations can have productivity effects



Some managerial Practices in Italy: the roleof performance for pay schemes

Damiani, Ricci and Pompei (2016a) analyze the effects ofperformance related pay (PRP) on both productivity and wages inItaly, in order to study the influence of this incentive scheme on thedistributive pattern

They pay attention to the presence of unions: are they favouring amore efficient management or simply extract a union wage premium?

From the Employer and Employee Surveys (RIL) conducted by theItalian Institute for the Development of Vocational Training forWorkers (ISFOL) in 2005, 2007 and 2010

They obtain an unbalanced panel of about 9,000 firms with 5 or moreemployees, localized in industry, services sectors and in all Italianregions

They find that PRP may significantly stimulate efficiency gains



Damiani, Ricci and Pompei (2016a):Distributive ImplicationsDeciles calculated by Instrumental Variable Treatment Effect QR ofFrolich and Melly

All#Firms# Unionized#Firms#

# #

#

.3.4

.5.6

.7.8

.9PR

P C

oeffi

cien

ts

1 2 3 4 5 6 7 8 9Quantile

Labour Productivity Wages

.3.4

.5.6

.7.8

.9PR

P C

oeffi

cien

ts

1 2 3 4 5 6 7 8 9Quantile

Labour Productivity Wages

PRP schemes contributed to temperate unit labor costsunions amplify the positive gap between labor efficiency and wages



Some managerial practices in Italy: the roleof other Human Resource practicesimplemented through Firm Level Bargaining

Damiani, Ricci and Pompei (2016b) investigate the effects of Firm LevelBargaining (FLB) on productivity performances of Italian family firms

They first estimate the association of family ownership and control withproductivity of Italian enterprises and find confirmation of bad performancesof both family ownership and management

...then they regress labour productivity on FLB to verify whether familycontrolled firms, adopting this type of agreements, may partially close theirefficiency gap with respect to their competitors

From the Employer and Employee Surveys (RIL) conducted by the ItalianInstitute for the Development of Vocational Training for Workers (ISFOL) in2007 and 2010

They obtain an unbalanced panel of about 7,700 firms with 5 or moreemployees, localized in industry, services sectors and in all Italian regions



Damiani, Ricci and Pompei (2016b): family management and labour

productivity

Quantile estimates OLS

Q10 Q25 Q50 Q75 Q90

Family management -0.116*** -0.094*** -0.063*** -0.067*** -0.072* -0.098***

(0.020) (0.016) (0.015) (0.024) (0.040) (0.019)

% executives -(0.053) 0.235*** 0.568*** 0.989*** 1.348*** 0.587***

(0.090) (0.083) (0.098) (0.082) (0.141) (0.083)

%white collars 0.338*** 0.399*** 0.436*** 0.490*** 0.576*** 0.424***

(0.035) (0.023) (0.014) (0.030) (0.039) (0.023)

% women -0.496*** -0.450*** -0.422*** -0.415*** -0.407*** -0.429***

(0.028) (0.025) (0.021) (0.019) (0.037) (0.023)

% fixed term contracts -0.569*** -0.469*** -0.370*** -0.250*** -0.209*** -0.403***

(0.056) (0.040) (0.032) (0.037) (0.044) (0.039)

Ln(firm seniority) (0.017) 0.025*** 0.024*** 0.028*** 0.032* 0.027***

(0.011) (0.007) (0.009) (0.010) (0.016) (0.008)

Ln(physical capital per employee) 0.097*** 0.103*** 0.103*** 0.118*** 0.138*** 0.121***

(0.008) (0.005) (0.003) (0.004) (0.007) (0.004)

Process innovation 0.040* 0.022 0.020* 0.001 -0.01 0.027**

(0.022) (0.019) (0.011) (0.012) (0.013) (0.012)

Product innovation (0.027) 0.013 -0.01 -0.008 -0.029 -(0.005)

(0.021) (0.016) (0.011) (0.011) (0.018) (0.011)

Export 0.108*** 0.084*** 0.064*** 0.083*** 0.080*** 0.091***

(0.015) (0.013) (0.012) (0.015) (0.028) (0.012)

Ln(size) 0.055*** 0.040*** 0.028*** 0.004 -0.023*** 0.019***

(0.008) (0.005) (0.006) (0.005) (0.008) (0.006)

Year 2010 -0.113*** -0.074*** -0.047*** -0.050*** -0.045** -0.073***

(0.018) (0.013) (0.011) (0.010) (0.019) (0.010)

Constant 9.072*** 9.269*** 9.481*** 9.622*** 9.680*** 9.344***

(0.078) (0.047) (0.040) (0.045) (0.087) (0.050)

NUTS1_level Dummies Yes Yes Yes Yes Yes Yes Sector Dummies Yes Yes Yes Yes Yes Yes R_2/PseudoR_2 0.193 0.184 0.177 0.179 0.183 0.297 Observations 9492

Notes: Robust (OLS) and bootstrap (Quantile Regression) standard errors in parentheses. .*** significant at .01 level; ** significant at .05 level; *significant at .10 level



Damiani, Ricci and Pompei (2016b): FLB and labour productivity

in FM Simultaneous Quantile estimates OLS

Q10 Q25 Q50 Q75 Q90

FLB 0.072*** 0.034* 0.057*** 0.069*** 0.109*** 0.077***

(0.025) (0.020) (0.020) (0.017) (0.031) (0.018)

% executives -0.117 0.183** 0.528*** 0.884*** 1.038*** 0.481***

(0.096) (0.086) (0.095) (0.110) (0.175) (0.087)

%white collars 0.358*** 0.400*** 0.436*** 0.491*** 0.595*** 0.427***

(0.040) (0.029) (0.023) (0.025) (0.041) (0.025)

% women -0.496*** -0.457*** -0.422*** -0.404*** -0.397*** -0.426***

(0.040) (0.028) (0.023) (0.024) (0.044) (0.026)

% fixed-term contracts -0.558*** -0.455*** -0.341*** -0.234*** -0.149** -0.382***

(0.094) (0.049) (0.038) (0.040) (0.070) (0.043)

Ln(firm seniority) (0.008) 0.019* 0.021** 0.026*** 0.026** 0.025***

(0.012) (0.010) (0.009) (0.008) (0.011) (0.009)

Ln(physical capital per employee) 0.092*** 0.103*** 0.101*** 0.117*** 0.136*** 0.119***

(0.007) (0.005) (0.003) (0.004) (0.007) (0.004)

Process innovation 0.053*** 0.027* 0.020* 0.01 -0.026 0.032***

(0.019) (0.014) (0.011) (0.014) (0.026) (0.012)

Product innovation (0.028) 0.01 -0.005 -0.007 -0.019 -0.003

(0.021) (0.016) (0.010) (0.014) (0.021) (0.012)

Export 0.094*** 0.083*** 0.064*** 0.075*** 0.075*** 0.087***

(0.022) (0.014) (0.012) (0.014) (0.022) (0.012)

Ln(size) 0.052*** 0.038*** 0.021*** -0.001 -0.036*** 0.013*

(0.010) (0.006) (0.005) (0.006) (0.012) (0.007)

Year 2010 -0.109*** -0.078*** -0.049*** -0.057*** -0.048** -0.074***

(0.015) (0.011) (0.011) (0.012) (0.020) (0.009)

Constant 9.027*** 9.201*** 9.468*** 9.567*** 9.689*** 9.284***

(0.085) (0.059) (0.046) (0.050) (0.088) (0.043)

NUTS1_level Dummies Yes Yes Yes Yes Yes Yes Sector Dummies Yes Yes Yes Yes Yes Yes R_2/PseudoR_2 0.192 0.181 0.172 0.174 0.175 0.175 Observations 8745



Higher-Quality Labour and Capital

We have seen that management practice is an unmeasured input thatdirectly enter TFP

Also other input qualities might not be included in standard measures oflabour and capital and end up to be embodied in TFP

As regards labour quality: education, gender, training, overall experience,and tenure at a firm, are not included in the number of employees or numberof hours worked, that is the standard labour input of a production function

In the last years, new detailed data (matched employer-employees databases)allowed to perform studies that focus on the labour quality-TFP relationship

Productivity is increasing in workers’ education as well as age in Finnishplants (Ilmakunnas, Maliranta, and Vainiomaki, 2004)

Worker education, gender, experience, and industry tenure are importantexplicative variables in the production function of Danish firms, even thoughaccounting for their influence only decreases the average within-industry90-10 percentile productivity ratio from 3.74 to 3.36 (Fox and Smeets,2011). Therefore they poorly explain the within-industry productivitydispersion.



Higher-Quality Labour and Capital (2)

Capital can also vary in quality in ways not captured with standard measures

If capital vintages differ from one another in how much technologicalprogress they embody, the common book-value-based capital stock measureswill tend to miss variations in average capital vintages across producers

It means assuming that all capital goods constituting the operating stock ofcapital have the same marginal contribution to output

In other words new and old capital goods contribute equally in conveyingtechnical progress

Such a view of capital denies de facto any connection between the pace ofinvestment and the rate of technological progress in the long run

Several studies have tried to measure the rate of capital-embodiedtechnological progress by carefully constructing measures of the distributionof capital vintages within plants or firms

Sakellaris and Wilson (2004) find that capital efficiency units grow at aconstant rate per year, which they estimate to be between 8 to 17 percentper year



Information Technologies and R&D

Information technology (IT) is the application of computers to store,retrieve, transmit and manipulate data, often in the context of a businessIT is a set of general purpose technologies that has more generallyinfluenced productivity patterns across multiple industries and countriesMany studies document that IT-related productivity gains play an importantrole in explaining aggregate U.S. productivity growth over the past couple ofdecadesInstead, European Union’s comparably sluggish productivity growth over thesame period can be explained in large part by the later emergence andsmaller size of IT investment in European economiesHowever, US-based multinationals operating in the European Union aremore productive than their EU counterparts, and this productivity advantageis primarily derived from IT capital and complementarity between IT capitaland human resources practicesSome authors document case studies where IT enhances the speed withwhich firms acquire a productivity advantage and displace less productivecompetitors more quickly. IT thus raises the volatility of firms’ performanceswithin industries



Information Technologies and R&D (2)

There is a long literature linking R&D and productivity, and recentadditions to it have focused on exploring the ties at the micro level.

The difficulty is in separating correlation from causation. There aremany reasons why more productive firms might do more R&D,suggesting that some of the causation may go the other way.

Some studies also find that firm-level uncertainty in the outcome ofR&D is considerable, much more so than with respect to the returnon physical capital investment

Their estimates suggest that engaging in R&D roughly doubles thedegree of uncertainty in the evolution of a producer’s productivitylevel.



Learning by Doing and Product Innovation

Productivity growth fostered by experience, often called learning-by-doing,has a long and rich history of study in the literatureBenkard (2000) studies the precipitous drop in the labor hours Lockheedneeded to assemble its L-1011 TriStar widebody aircraft: from 1mln personhours to 0.5 mln by the 30th plane, and again 0.25 mln after the 100th oneBenkard particularly focus on learning rate:how fast past productionincreases productivity (decreases unit labor requirements)...... and forgetting rate:which is how fast the knowledge stock built bylearning depreciatesForgetting is quantitatively important in this setting: Benkard estimates thatalmost 40 percent of the knowledge stock depreciates each yearForgetting rate depends on : labour turnover and shift to a new variantof the planeMultidesign or multi-product processes Thornton and Thompson (2001)and Levitt, List, and Syverson (2011) investigate what types of experiencematter in productivity growth from learning by doingCross-model learning spillovers in shipyards and auto assembly plantsplayed a modest role



Learning by Doing and Product Innovation (2)

Innovations in product quality may not necessarily raise the quantity of outputper unit input, but they can increase the product price and, therefore, the firm’srevenue per unit input

Rasmus Lentz and Dale T. Mortensen (2008) use Danish firm-level data toestimate a model of firms’s product innovation

Product innovation spurs industry dynamics through productivity growth

They find that about 75 percent of aggregate productivity growth comes fromreallocation of inputs (employment in their setup) to innovating firms

As regards this 75 percent: One third comes from Entry and exit channels andTwo-thirds from Inputs moving toward growing firms (and hence innovating firmsas seen through the lens of their model) from firms that lose market share

Balasubramanian and Sivadasan (2011) and Redding and Schott (2010) show thatboth patenting and variety of products that firms offer increase the TFP


External Determinants

These external drivers can impact both the so-called ”within” and ”between”components of aggregate productivity growth

The within component comes from individual producers becoming more efficient

The between component arises when more efficient producers grow faster thanless efficient ones, or when more efficient entrants replace less efficient exitingbusinesses

Why external forces matter? The most basic producer theory, after all, says anyprofit minimizing firm minimizes its cost of producing its chosen quantity

1 Spillovers: other firms’ production practices influence another business’sproductivity level

2 Darwinian selection in the firm’s market: environmental factors change theminimum productivity level necessary for profitable operation

3 Disruption costs and competition affect the incentives to innovate and to boostproductivity



Productivity Spillovers

Producer practices can have spillover effects on the productivity levels of other firms

Many papers suggest that spillovers exist and operate through various mechanisms, though theobserved productivity dispersion also makes clear that substantial frictions to the diffusion andreplication of best practices remain

Spillovers occur by means of agglomeration mechanisms like thick-input-market effects orKnowledge transfers

Enrico Moretti (2004) explores agglomeration-type productivity in the US by estimating aplant-level production function that includes the share of workers in other industries in themetro area who have completed some college

He interprets the estimated significant marginal product of this outside educated labor as aproductivity spillover

Several studies have focused specifically on the role of knowledge transfers:it is doubtful thatproductivity-enhancing practices are completely excludable; businesses cannot always keep everyfacet of their production process secret

Griffith, Harrison, and Van Reenen (2006) show that the geographic location of a firm’s R&Dactivity matters

U.K. firms with a greater R&D presence in the United States have faster overall productivity



Competition and Product Market Regulation

Competition drives productivity through two key mechanisms:

1 Darwinian selection among producers with heterogeneous productivity levels: competitionmoves market share toward more efficient producers, shrinking relatively high-cost firms/plants,sometimes forcing their exit, and opening up room for more efficient producers

2 Efficiency increases within plant/firms: heightened competition can induce firms to take costlyproductivity raising actions that they may otherwise not

Studies on competitive pressure and productivity can also be grouped in those dealing withintra-market competition and those focusing on international trade

As regards intra-market competition, Syverson (2004) investigates the connection betweencompetition and productivity in a case study of the ready-mixed concrete industry and interpretit as Darwinian selection

It is harder for inefficient concrete producers to be profitable in dense markets because, if theycharge the high prices necessary to cover their costs, customers (i.e. Construction sector) caneasily shift to their more efficient competitors

Bloom, Draca, and Van Reenen (2011) look at how Chinese import competition affectedproductivity and innovation in twelve European countries between 1996 and 2007

In aggregate,Chinese trade competition increased aggregate TFP in these markets through bothwithin- and between-firm (selection) effects



Competition and Product Market Regulation(2)Many studies highlight that excessive regulation of the product markets hurtsproductivity:

Shi Qi, and Schmitz (2009) show how regulations in place for decades in the U.S. sugarmarket (Sugar Act, 1934) destroyed incentives to raise productivity

Farmers received a flat payment per ton of sugar contained in their beets, so theiroptimal response was to simply grow the largest beets possible

The problem is that refining larger beets into sugar is less efficient. As beets grow larger,their sugar-to-pulp ratio falls

Yields began to climb again immediately after the act was repealed

Other studies show that moving plants away from a traditional cost-plus regulatedmonopoly structure into alternative forms (i.e. ”incentive regulation” programs, whereregulators explicitly tie operators’ earnings to the achievement of particular operatingefficiencies, favour the productivity enhancement

List and Syverson (2011) show how environmental regulations (the U.S. Clean Air ActAmendments specifically) reduce manufacturing plants’ productivity levels



Input MarketsIf one thinks of competition as flexibility in product markets it is logical to supposethat flexible input markets might also raise productivity levels

The more easily inputs can move toward firms experiencing growth in demand, whichwill typically be higher-productivity businesses due to the forces described above, thefaster the reallocation mechanism works

The institutional features of input markets, such as the roles of unions and the structureof the financial sector, have an ambiguous theoretical impact on flexibility

Maksimovic and Phillips (2001) investigate the market for U.S. manufacturing plantsthemselves, as productive assets, and find that, on average, a plant’s productivity risesafter the sale

Petrin and Sivadasan (2010) measure the difference between Chilean plants’ marginalproducts of labor and their average wages...

...and find that a particular legislative change that raised firing costs was associated withan increase in the mean gap, suggesting the legislation reduced allocative efficiency

Bartelsman, Haltiwanger, and Scarpetta (2009) look at the success of allocation acrossseveral countries and find that well functioning markets reallocate output to moreproductive plants, leading to a positive correlation between output share and productivity



Importance of Demand

Productivity as actually measured in producer microdata generallyreflects more than just supply-side forces

Because producer-specific prices are unobserved in most business levelmicrodata, output is typically measured by revenue divided by anindustry-level deflator

If prices reflect in part idiosyncratic demand shifts or market powervariation across producers then high ”productivity” businesses may not beparticularly technologically efficient

A new strand of research has begun to extend the productivity literature toexplicitly account for such idiosyncratic demand effects as well

The work to this point indicates that demand factors are indeed important.

They exert a considerable influence on businesses’ growth and survival


determinants of productivity at firm- and...

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