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Developing countries are increasingly concerned about improving country competitiveness and productivity. Investment Climate surveys (ICs) at the firm level, are becoming the standard way for the World Bank to identify key obstacles to country competitiveness. This paper develops a general to specific econometric methodology, based on firm level observable fixed effects that generate robust investment climate effects (elasticities) on total factor productivity (TFP). By robust IC elasticities on TFP we mean elasticity estimates with equal signs and of similar magnitudes for several competing TFP measures. We apply this econometric methodology to the IC survey of Costa Rica showing how robust the investment climate effects are for several measures of TFP when conditioning on relevant plant-level information that is usually unobserved. For the economic evaluation we estimate the marginal effects of each IC variable on TFP as well as their IC impacts on average TFP obtaining important economic differences. These IC estimates are obtained from five blocks of IC variables, (i) infrastructure, (ii) red tape, corruption and crime, (iii) finance and corporate governance, (iv) quality, innovation and labor skills and (v) other control variables, could be used as benchmarks to assess cross-country IC assessments of TFP. Alvaro Escribano and Jorge Pena acknowledges funding from The World Bank. Alvaro Escribano acknowledge funding from the Spanish Ministry of Economy, Industry and Competitiveness (ECO2015-68715-R, ECO2016-00105-001), Consolidation Grant (#2006/04046/002), and Maria de Maeztu Grant (MDM 2014-0431).

Developing countries are increasingly concerned about improving country competitiveness and productivity, as they face the increasing pressures of globalization and attempt to improve economic growth and reduce poverty. Among such countries, Investment Climate surveys (ICs) at the firm level, have become the standard way for the World Bank to identify key obstacles to country competitiveness, in order to prioritize policy reforms for enhancing competitiveness. Given the surveys objectives and the nature and limitations of the data collected, this paper discusses the advantages and disadvantages of using different total factor productivity (TFP) measures. The main objective is to develop a methodology to generate robust investment climate impacts (elasticities) on TFP under alternative measures. The paper applies it to the data collected for ICs in four developing countries: Costa Rica, Guatemala, Honduras and Nicaragua. Observations on logarithms of the production function variables are pooled across three countries (Guatemala, Honduras and Nicaragua). Endogeneity of the production function inputs and of the investment climate variables is addressed by using observable firm level information, a variant of the control function approach, considering IC variables as proxy and also by aggregating certain investment climate variables by industry and region. It is shown that by using this methodology it is possible to get robust IC “elasticities” on TFP for more than ten different TFP measures. The robust IC elasticity estimates for the five countries show how relevant the investment climate variables are to explain the average productivity of each country. IC variables in several categories (red tape, corruption and crime, infrastructure and, quality and innovation) account for over 30 percent of average productivity. The policy implications are clear: investment climate matters and the relative impact of the various investment climate variables helps indentifying where reform efforts should be directed in each country. It is argued that this robust methodology can be used as a benchmark to assess cross-country productivity effects in other IC surveys. This is important since similar firm-level IC surveys on several sectors (manufacturing, services, etc.) are now available at the World Bank for more than 65 developing countries.

Developing countries are increasingly concerned about improving country competitiveness and productivity, as they face the increasing pressures of globalization and attempt to improve economic growth and reduce poverty. Among such countries, Investment Climate surveys (ICs) at the firm level, have become the standard way for the World Bank to identify key obstacles to country competitiveness, in order to prioritize policy reforms for enhancing competitiveness. Given the surveys objectives and the nature and limitations of the data collected, this paper discusses the advantages and disadvantages of using different total factor productivity (TFP) measures. The main objective is to develop a methodology to generate robust investment climate impacts (elasticities) on TFP under alternative measures. The paper applies it to the data collected for ICs in four developing countries: Costa Rica, Guatemala, Honduras and Nicaragua. Observations on logarithms of the production function variables are pooled across three countries (Guatemala, Honduras and Nicaragua). Endogeneity of the production function inputs and of the investment climate variables is addressed by using observable firm level information, a variant of the control function approach, considering IC variables as proxy and also by aggregating certain investment climate variables by industry and region. It is shown that by using this methodology it is possible to get robust IC “elasticities” on TFP for more than ten different TFP measures. The robust IC elasticity estimates for the five countries show how relevant the investment climate variables are to explain the average productivity of each country. IC variables in several categories (red tape, corruption and crime, infrastructure and, quality and innovation) account for over 30 percent of average productivity. The policy implications are clear: investment climate matters and the relative impact of the various investment climate variables helps indentifying where reform efforts should be directed in each country. It is argued that this robust methodology can be used as a benchmark to assess cross-country productivity effects in other IC surveys. This is important since similar firm-level IC surveys on several sectors (manufacturing, services, etc.) are now available at the World Bank for more than 65 developing countries.

Investment climate Surveys are valuable instruments that improve our understanding of the economic, social, political, and institutional factors determining economic growth, particularly in emerging and transition economies. However, at the same time, they have to overcome some difficult issues related to the quality of the information provided; measurement errors, outlier observations, and missing data that are frequently found in these datasets. This paper discusses the applicability of recent procedures to deal with missing observations in investment climate surveys. In particular, it presents a simple replacement mechanism -- for application in models with a large number of explanatory variables -- which in turn is a proxy of two methods: multiple imputations and an export-import algorithm. The performance of this method in the context of total factor productivity estimation in extended production functions is evaluated using investment climate surveys from four countries: India, South Africa, Tanzania, and Turkey. It is shown that the method is very robust and performs reasonably well even under different assumptions on the nature of the mechanism generating missing data.

This paper provides a systematic, empirical assessment of the impact of infrastructure quality on the total factor productivity (TFP) of African manufacturing firms. This measure is understood to include quality in the provision of customs clearance, energy, water, sanitation, transportation, telecommunications, and information and communications technology (ICT). Microeconometric techniques to investment climate surveys (ICSs) of 26 African countries are carried out in different years during the period 2002–6, making country-specific evaluations of the impact of investment climate (IC) quality on aggregate TFP, average TFP, and allocative efficiency. For each country the impact is evaluated based on 10 different productivity measures. Results are robust once controlled for observable fixed effects (red tape, corruption and crime, finance, innovation and labor skills, etc.) obtained from the ICSs. African countries are ranked according to several indices: per capita income, ease of doing business, firm perceptions of growth bottlenecks, and the concept of demeaned productivity (Olley and Pakes 1996). The countries are divided into two blocks: high-income-growth and low-income-growth. Infrastructure quality has a low impact on TFP in countries of the first block and a high (negative) impact in countries of the second. There is significant heterogeneity in the individual infrastructure elements affecting countries from both blocks. Poor-quality electricity provision affects mainly poor countries, whereas problems dealing with customs while importing or exporting affects mainly faster-growing countries. Losses from transport interruptions affect mainly slower-growing countries. Water outages affect mainly slower-growing countries. There is also some heterogeneity among countries in the infrastructure determinants of the allocative efficiency of African firms.