Do Regions Benefit from an Open Economy?

Ernesto M. PerniaSchool of Economics University of the Philippines

Luncheon Speech2015 BSP-UP Professorial Chair Lectures19 October 2015

Introduction: roots of PH’s spatial development

Data and approach

Patterns of regional development

Openness, regional growth, and poverty reduction

-- Econometric analysis & results

Conclusion and policy implications

Outline

Introduction External influence on national urban systems dates back to colonial times.Cities were the strategic contact points between colonizer and colony.Evolution of ports and transport systems was strongly shaped by trade and investment decisions of colonial authorities.Indeed, the geographic location of ports was critical to choice of primary and secondary urban centers.

Introduction (cont’d)New globalization trends, incl. Aseanintegration, exert probably stronger and different types of impactsIn perspective, urban and spatial development in the Philippines the result of

colonial legacy – reducción … debajo de lascampanas … under Spanish regime. domestic market forces and policies.global forces• capital, trade, and labor flows• technology and information.

Table 1. Levels of urbanization in Asean(% urban of total population)

ASEAN 8 1990 2000 2005 2010 2015 2000-2005

2005-2010

2010-2015

Cambodia 15.5 18.6 19.2 19.8 20.7 2.4 2.11 2.65

Indonesia 30.6 42.0 45.9 49.9 53.7 3.23 3.06 2.69

Lao PDR 15.4 22.0 27.4 33.1 38.6 5.84 5.79 4.93

Malaysia 49.8 62.0 66.6 70.9 74.7 3.41 3.06 2.66

Myanmar 24.6 27.0 28.9 31.4 34.1 2.11 2.33 2.49

Philippines 48.6 48.0 46.6 45.3 44.4 1.43 1.12 1.32

Thailand 24.4 31.4 37.5 44.1 50.4 4.57 3.48 2.97

Viet Nam 20.3 24.4 27.3 30.4 33.6 3.2 3.1 3.0

Source: U.N., World Urbanization Prospects : The 2014 Revision (N.Y., 2014).

Focus on effects of economic openness on:

balanced/unbalanced regional developmentregional income growthpoverty reduction or welfare of the

poor.

Introduction (cont’d)Two views on economic openness and regional development:

economic openness & urban concentration inversely related as trade spurs growth of countryside, given that exports are not linked to the domestic market (Krugmanand Livas 1996 – new economic geography models). trade and FDI reinforce urban primacy as economic activity is concentrated in capital metropolis and inter-city infrastructure is inadequate (e.g., Fuchs and Pernia 1987 on Asia; Rivas 2007 on Mexico).

Data and ApproachData on Philippines’ 14 regions in 1988-2000 and 17 regions in 2009-2013.Significant liberalization measures introduced, effecting beginning in 1994… GDP growth of over 5% in 1994-1997 and to >6% in 2010 onward …

GRDP data are from National Income Accounts, socioeconomic and fiscal data from relevant government agencies, household data on poverty from Family Income and Expenditure Surveys, etc.

Discern general patterns across regions and over time.

Econometric analysis.

Patterns of Regional DevelopmentEconomic Indicators

Regional imbalance appears to be persisting• Metro Manila (MM or NCR), as expected,

continues to have the highest income per capita @ Php196K in 2013

• widening interregional income differential– MM’s GRDP per capita close to 2.8 times

national average, about 2.3 times that of next highest (CALABARZON), and more than 13 times the poorest region (ARMM)

• MM’s share in GDP rising from 30% in 1988 to 36.3% in 2013.

Table 2. Gross Regional Domestic Product (GRDP), Regional Share,and Growth of GRDP (constant 2000 prices)

2009 2011 2013 2009 2011 2013 2009-11 2011-13PHILIPPINES PHILIPPINES 58,198.6 62,328.2 68,897.1 7.1 10.5

NCR METRO MANILA 162,320.9 173,057.1 195,806.4 35.8 35.6 36.3 6.6 13.1 CAR CORDILLERA 70,671.8 73,490.2 76,284.4 2.1 2.1 1.9 4.0 3.8

I ILOCOS 35,812.6 38,086.6 42,234.9 3.2 3.1 3.1 6.3 10.9 II CAGAYAN VALLEY 31,518.5 32,016.6 36,017.4 1.9 1.8 1.8 1.6 12.5 III CENTRAL LUZON 46,545.9 52,372.2 55,934.9 8.8 9.3 9.0 12.5 6.8 IVA CALABARZON 73,270.7 78,230.6 84,656.6 17.1 17.4 17.4 6.8 8.2 IVB MIMAROPA 37,724.2 37,282.6 38,423.3 1.9 1.8 1.7 (1.2) 3.1 V BICOL 20,580.3 20,978.7 23,873.1 2.1 2.0 2.0 1.9 13.8 VI WESTERN VISAYAS 30,942.5 33,296.3 36,414.3 4.1 4.1 4.0 7.6 9.4 VII CENTRAL VISAYAS 44,993.4 52,192.5 59,425.4 5.7 6.2 6.3 16.0 13.9 VIII EASTERN VISAYAS 36,058.1 36,784.4 35,534.5 2.8 2.6 2.2 2.0 (3.4) IX ZAMBOANGA PENINSULA 34,353.0 33,488.7 38,064.3 2.2 2.0 2.0 (2.5) 13.7 X NORTHERN MINDANAO 46,818.4 50,506.5 55,060.0 3.7 3.8 3.7 7.9 9.0 XI DAVAO REGION 46,721.3 49,111.6 54,359.2 3.9 3.8 3.8 5.1 10.7 XII SOCCSKSARGEN 36,688.2 37,533.5 41,995.8 2.8 2.7 2.8 2.3 11.9 XIII CARAGA 24,264.4 28,202.8 32,751.7 1.1 1.2 1.2 16.2 16.1

ARMM MUSLIM MINDANAO 13,867.3 14,271.4 14,565.6 0.8 0.8 0.7 2.9 2.1

REGION / YEAR

Per Capita GDP (in pesos) Regional Share (%) GRDP growth rate

Regional Patterns…Most of the special economic zones (SEZs) are located in 4 regions: NCR, CALABARZON, Central Luzon, and Central Visayas.The 4 regions hosting the SEZs are the main recipients of both foreign and local investments.Pattern of exports reveal essentially the same relative dominance of the 4 regions, though exports appear more spatially dispersed.NCR’s primacy in exports and investments appears to be waning.

Regional Patterns…Social Indicators

Social development reflects not only region’s economic performance but also efficacy of public spending for social services at the local level• inter-regional disparities not as sharp as

economic indicators• Mindanao regions continue to fare poorly

relative to other regions in terms of education and health indicators.

Regional Patterns…Poverty Indicators

• Poverty incidence at national level on a slow downtrend, 27.3% (2000) to 25.2% (2012).

• At the regional level, poverty incidence is lowest in MM (3.9%) and highest (and rising) in ARMM (55.8) and Eastern Visayas (45.2) in 2012.

• Similar pattern shown by consumption expenditure per capita (welfare) of poorest quintile – even falling for some Mindanao regions and Eastern Visayas in 2012 from 2006.

• Elasticity estimate from cross-regional OLS regression is 0.42, suggesting a 10% increase in regional incomes raises well-being of the poor by just 4.2%, implying inequality-increasing effect of regional income growth.

Table 3. Poverty Incidence and Expenditure Per Capita of Poorest Quintile

2009 2012 2009 2012

PHILIPPINES PHILIPPINES 26.3 25.2 153.0 148

NCR METRO MANILA 3.6 3.9 274.0 261

CAR CORDILLERA 25.1 22.8 154.0 147

I ILOCOS 22.0 18.5 133.0 128

II CAGAYAN VALLEY 22.5 22.1 122.0 107

III CENTRAL LUZON 13.7 12.9 160.0 160

IVA CALABARZON 11.9 10.9 187.0 187

IVB MIMAROPA 34.5 31.0 103.0 104

V BICOL 44.2 41.1 116.0 108

VI WESTERN VISAYAS 30.8 29.1 122.0 123

VII CENTRAL VISAYAS 31.0 30.2 134.0 128

VIII EASTERN VISAYAS 42.6 45.2 106.0 99

IX ZAMBOANGA PENINSULA 45.8 40.1 96.0 89

X NORTHERN MINDANAO 40.1 39.5 116.0 103

XI DAVAO REGION 31.4 30.7 119.0 115

XII SOCCSKSARGEN 38.3 44.7 107.0 103 XIII CARAGA 54.4 40.3 101.0 99 ARMM MUSLIM MINDANAO 47.4 55.8 81.0 80

REGION / YEAR

Average Expenditure in thousands (2006=100)

Regional Patterns…Summary thus far

MM remains pre-eminent in the country’s economic and social landscape.Regional disparities are revealed more sharply by economic indicators than by social indicators• narrow differentials in social indicators suggest

only slight variations in efficacy of social policy at local levels, regardless of regional economic differentials.

• regional poverty rates vary widely and are more closely associated with economic than with social indicators.

Openness and other Factors

Regional economic growth

Poor’s welfare

GRDP per capita

Consumption expenditure per capita of the poor

OpennessInfrastructureHuman capitalPolicy efficacy

Figure 1. Determinants of REG and PW

Estimating equations PCEPOORrt = PCEPOORrt (GRDPrt, LOCALrt, ICONDr) (1)GRDPrt = GRDPrt (LOCALrt, LOCALrt-1, OPENrt) (2) OPENrt = OPEN rt (LOCALrt, LOCALrt-1, OPENrt-1, GRDPrt)(3)

where:PCEPOORrt = per capita expenditure of the poor in region r at time t

GRDPrt = income of region r at time tOPENrt = economic openness (exports-GRDP ratio) in region r at time t

LOCALrt = local factors in region r at time tICONDr = initial conditions of region r

Explanatory notesEquation 1 shows how the welfare of the poor is influenced by the region’s income, local factors, and initial conditions. Equations 2 and 3 take into account the endogeneity of GRDP and economic openness as both are affected by each other and by local factors.

Equations 1-3 are estimated using the three-stage least squares (3SLS) method. The 3SLS estimation procedure takes into account not only the endogeneity of the three variables (per capita expenditure of the poor, regional income, and exports) but also the interaction between equations through the covariance matrix of the equations’ disturbances.

For the estimation, we use panel data on the 14 regions for the years 1988, 1991, 1994, 1997, and 2000 (i.e., four 3-year intervals), as well as 2009-2013 on 17 regions . Our empirical model is constrained by the available data. To test for dynamic effects, current as well as lagged values are used.

Empirical results

Regional net exports are positively influenced by

previous export performancealso GRDP per capita (acc. to more recent data)agricultural terms of trade previous-period local development expendituresnumber of SEZssignificant primacy dummy implies that MM dominates in exports and re-exports.

Table 4. Determinants of Economic Openness, GRDP per capita, and Welfare of the Poor (1988-2000)Variable Ln Exports/

GRDPs.e. Ln GRDP per Capita s.e. Ln Mean Exp./ Capita of

bottom quintiles.e

(1) (2) (3)

Endogenous

Ln GRDP per capita -0.165 0.410 0.198 ** 0.079

Ln Exports-GRDP Ratio 0.044 ** 0.019

Lagged Ln Exports-GRDP Ratio 0.869 ** 0.044

Local Factors

Lagged Ln Investment-GRDP Ratio -0.022 0.047

Ln Social Expenditures per capita 0.031 * 0.016

Lagged Ln Social Exp. Per capita 0.142 ** 0.058

Lagged Ln Dev't Exp. Per Capita 0.184 ** 0.087 0.016 0.050

Number of Special Economic Zones 0.047 ** 0.010

Terms of Trade 2.204 ** 0.898

Average Schooling Years of Household Heads 0.115 ** 0.039

Initial Conditions

Cohort Survival Rate for Secondary Education 0.010 ** 0.003

Road Density 0.125 ** 0.027

% of Households with Electricity 0.009 ** 0.001

Primacy (NCR=1; 0 otherwise) 2.411 ** 1.081 0.570 ** 0.185

Constant - 1.907 3.629 7.870 ** 0.351 4.336 ** 0.671

Equation R2 chi2 Equation R2 chi2

Ln Mean Exp. of Bottom Quintile 0 .828 366.543 Ln Exports 0.908 636.8473

Ln GRDP per capita 0 .682 133.097* significantly different from zero at 10 percent level** significantly different from zero at 5 percent level or lower

Table 5.. Determinants of Economic Openness, GRDP, and Welfare of the Poor (2009-2013)

Variable Net Exports/ GRDP

Std Error Ln GRDP per capita Std Error Ln mean exp. Per capita of bottom quintile

Std Error

(1) (2) (3)EndogenousLn GRDP per capita 0.0917** 0.0368 0.2474***  0.0509Net Exports‐GRDP Ratio 1.2220*** 0.0816Lagged Net Exports/GRDP Ratio 0.8162***  0.0533

Lagged Ln Investment‐GRDP Ratio ‐0.0003  0.0022

Local Factors

Number of special economic zones 0.0000  0.0000

Initial ConditionsPoverty Incidence ‐0.0214***  0.0021Cohort survival rate for secondary education of females 0.7533  0.6872Cohort survival rate for secondary education of males 2.2344***  0.8613Life expectancy of females ‐0.0300  0.0391Life expectancy of males 0.0406 0.0431% of Paved Roads 1.1627***  0.2794% of Households with Electricity 1.3771***  0.3976Primacy ‐0.0722  0.0573 0.5336*** 0.0971Constant ‐0.3993** 0.1625 4.5073***  0.0597 5.0238*** 1.3783

Equation R2 chi2

Ln Mean Exp. Of Bottom Quintile 0.7528 213.36Ln GRDP per capita 0.9209 806.71 Net Exports/GRDP 0.9362 993.58 

* Significantly different from zero at 10% level** Significantly different from zero at 5% level*** Significantly different from zero at 1% level

Determinants…Regional income growth is influenced by

trade opennessprevious period’s spending for social serviceshuman capital stockprimacy dummy implies that NCR maintains income-dominance over all regions.Incidentally, the Economist (January 24-30, 2015, pp. 63-65) reports research (Bjorn Lomborg, Copenhagen Consensus Center) showing that trade liberalization, in general, by far results in the biggest benefit (bang per buck) ($2,011/$1) spent among various development policy measures; next is access to contraception ($120/$1) –better than spending on, e.g., environment as most developing countries actually negligible polluters globally.

Determinants…Well-being of the poor is positively influenced by

economic growthpublic spending for social services, including agrarian reforminfrastructure (electricity, roads) human capital stock.

No clear evidence on direct link from trade openness to poor’s welfare/incomes, except thru economic growth (Krueger & Berg 2002; Winters et al. 2004).

Conclusion and Policy ImplicationsEconomic openness is beneficial to regional economic growth and – through growth – poor’s welfare/poverty reduction.But, due to unbalanced regional development, to begin with, effect of openness limited to relatively developed regions, incl. corollary effect on poverty.Thus, growth of such areas as CALABARZON, Central Luzon, CAR, and Central Visayas appreciably attributable to external factors (trade & investment, not to mention overseas Filipino remittances).External factors by themselves cannot be relied upon to bring about more balanced regional development or narrower spatial disparities.

Conclusion…To foster more balanced development, public policy must take a more deliberate lead and vigorously encourage the private sector to play a more active role.Good physical and social infrastructures are crucial, as are strong national and local governance, and a conducive investment climate.Only then, perhaps, can openness exert a wider spread effect on regional growth and poverty reduction.

Thank you!