Luis Servén The World Bank ECLAC January 2005 Latin America’s infrastructure gap: a macroeconomic perspective.

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Presentation transcript:

Luis Servén The World Bank ECLAC January 2005 Latin America’s infrastructure gap: a macroeconomic perspective

1.The changing policy framework 2.The infrastructure gap 3.The output cost 4.The lessons Plan

Until the 1970s, the public sector dominated infrastructure provision in both industrial and developing countries. Since the 1980s (earlier in Chile and the UK) Latin America led the worldwide drive towards opening up of infrastructure to private initiative – in various forms and extents. The drive was propitiated by a hardening of fiscal discipline in response to financial instability and macroeconomic crises In most countries, the fiscal retrenchment led to a sharp contraction of public infrastructure investment (similarly to the post-Maastritch fiscal adjustment in the EU) The changing policy framework

Latin America’s fiscal adjustment: Contribution of consumption and investment The changing policy framework

Latin America: Total investment in Infrastructure (weighted average of 7 countries, percent of GDP)

The changing policy framework Latin America: Total investment in Infrastructure (6 major countries, percent of GDP)

The changing policy framework

The private sector response Private initiative surged in the 1990s -- but with diversity across industries (and countries) Strong response in telecommunications, much less in transport. Evidence of public-private complementarity, not only substitution: countries maintaining higher public investment attracted more private investment (Chile, Bolivia, Colombia) The rise in private investment was not enough for asset accumulation to keep up with other world regions The investment fall contributed to widen Latin America’s infrastructure gap – in terms of quantity and quality -- widened over the 1980s and 1990s The changing policy framework

Capacity change Investment Brazil: the power sector The changing policy framework

The infrastructure gap

Perceived infrastructure quality (Medians by region, 2000)

Why do we care about infrastructure ? The availability and quality of infrastructure services is key for productivity and profitability Robust association between infrastructure availability and aggregate output / growth within and across countries Partly driven by reverse causality (growth encourages demand for infrastructure services) But there is broad agreement that infrastructure development has a strong causal effect of on economic development. Evidence that infrastructure development helps reduce income inequality – makes it easier for the poor to access economic opportunities, jobs, health and education. The output cost

Source: Calderón and Servén (2004b)

Source: Calderón, Easterly and Servén (2003)

Source: Calderón and Servén (2004b)

What is the contribution of infrastructure services to aggregate output and/or its growth rate ? Three main empirical approaches in the literature: 1.Empirical growth models 2.Augmented production (or cost) function 3.VARs Caveats: -- technical problems often severe (identification / reverse causality, spurious regressions…) -- all else equal: the costs of “getting there” are not explored – large tax rises or cuts in other expenditures that may have an output cost… The output cost

The long-run growth approach: Adding infrastructure into a standard growth regression Infrastructure usually proxied by telecommunications indicators (e.g., Easterly 2001, Loayza et al 2003) Calderón and Servén 2004b: panel of 100+ countries, 40 years  Consider both infrastructure quantity and quality  Synthetic infrastructure indicator: first principal component of {power, roads, telecom} – accounts for 80% of their variance.  Endogeneity: identification via GMM-IV with (a) internal instruments; (b) demographic variables  Growth contribution of infrastructure quantity and quality is statistically and economically significant. The output cost

Source: Calderón and Servén 2004b Additional growth in LAC countries due to increased infrastructure development

The augmented production function approach: Unlike VARs and growth regressions, it is a structural approach Y = F (K, H, Z); K = physical capital; H = human capital (often omitted) ; Z = infrastructure capital (power, phone lines, roads) Productive services assumed proportional to asset stocks In actual data, Z often is already included in K: The coefficient on Z captures the return differential on Z over K In addition to usual reverse causality problem, spurious correlation problem when using time series: nonstationarity of Y, K, Z leads to huge infrastructure coefficient estimates (Aschauer 1990) The output cost

The augmented production function approach Calderón and Servén 2005: panel time-series estimation for 90 countries, 40 years. Spurious regression problem does not arise here (due to large N) Only one long-run relation found – resolves identification problem Pooled and country-specific estimates – permit assessing heterogeneity across countries / regions Synthetic index and disaggregated infrastructure assets Results broadly similar to Calderón, Easterly and Servén 2003 – in spite of very different approach (GMM-IV to deal with identification; first-differencing to deal with nonstationarity) The output cost

Estimated (log) infrastructure coefficients (DOLS estimates, , synthetic index) The output cost Source: Calderón and Servén 2005

Country-specific estimates [Synthetic Infrastructure Index, GLS--PIC (1,1)] The output cost Source: Calderón and Servén 2005

The estimated return on infrastructure assets is significantly higher than that on other physical capital in the vast majority of countries. Infrastructure has significantly lower returns than other capital only in 3 out of 89 countries [none in LAC] Across LAC countries, some heterogeneity too: The differential return on overall infrastructure is significantly higher than average in Peru, Mexico, Colombia… Differences also across assets – e.g., the differential return on power generation capacity is significantly lower than average in Paraguay, but higher in Brazil The output cost

Estimated (log) infrastructure coefficients (DOLS estimates, ) The output cost Source: Calderón and Servén 2005

The output cost Source: Based on Calderón and Servén 2005 The cost of the widening infrastructure gap: EAP vs LAC

(1) Fiscal adjustment, as commonly measured and enforced, tends to have an anti-investment bias One (not the only) major factor is the use of inappropriate fiscal rules targeting liquidity, the cash deficit and gross public debt – rather than solvency and net worth, which are key to fiscal sustainability. Infrastructure projects have a negative short-run liquidity effect -- it takes time to build the assets and get the returns. The focus on fiscal liquidity discourages such projects – even if they are consistent with good public economics; i.e., they enhance solvency. The lessons

(2) Infrastructure investment cuts represent an inefficient fiscal adjustment strategy The direct effect of the spending cut is to raise liquidity and public sector net worth But there is an opposing indirect effect: less infrastructure means less output and lower fiscal revenues tomorrow The indirect effect offsets partly the direct effect – and can even make fiscal adjustment self-defeating. The lessons

Summary Latin America’s infrastructure gap widened in the 1980s and early 1990s, at a substantial cost in terms of output and productivity. A major factor in the process was the investment slowdown – caused by a public investment decline not offset (except in telecom) by private sector participation. The public investment compression reflected a biased and inefficient fiscal adjustment, encouraged by rules targeting liquidity and debt rather than solvency and net worth. Ensuring adequate room for productive spending requires fiscal rules that reconcile solvency and growth.

End

The changing policy framework Fiscal discipline has led to a public investment fall not only in developing countries – also in the EU The fiscal targets imposed in the Maastritch Treaty contributed to a decline in public investment across Europe: Out of 9 countries exceeding the Maastritch deficit limit in 1992, 8 met it in Public investment had fallen in all 8 ! Infrastructure investment fell along with the total

The changing policy framework