Assesing the Impact of the Investment Climate on Productivity Using Firm-Level Data: Methodology and the Cases of Guatemala, Honduras, and Nicaragua

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 Assessments (ICA) have become a standard instrument for identifying key obstacles to country competitiveness and imputing their impact on productivity, in order to prioritize policy reforms for enhancing competitiveness. Given the survey objectives and the nature and limitations of the data collected, this report discusses the advantages and disadvantages of using different productivity measures based on data at the firm level. The main objective is to develop a methodology to appropriately estimate, in a robust manner, the productivity impact of the investment climate variables. To illustrate the use of this methodology, the report applies it to the data collected for ICAs in three countries: Guatemala, Honduras and Nicaragua. Observations in logarithms (logs) of the variables, and not in rates of growth, are pooled from all three countries. The econometric analysis is done with variables in logs to reduce the impact of measurement errors and allow inclusion of as many observations as possible since the “panel” data set is very unbalanced. Endogeneity of the production function inputs and of the investment climate variables is addressed by using a variant of the control function approach, based on individual firm information, and by aggregating investment climate variables by industry and region. It is shown that it is possible to get robust results for 10 different productivity measures, if one follows a consistent econometric methodology of specification and estimation. For policy analysis, the report strongly recommends using those results of investment climate variables on productivity that are robust for most of the productivity measures. Efficiency aspects of firms in each country are also analyzed. Finally, the results are decomposed to obtain country-specific impacts and establish corresponding priorities for policy reform. The actual estimates for the three countries show the level of significance of the impact of investment climate variables on productivity. Variables in several categories, red tape and infrastructure in particular, appear to account for over 30 percent of productivity. The policy implications are clear: investment climate matters enormously and the relative impact of the various investment climate variables indicates where reform efforts should be directed. Given the robustness of the results, it is argued that the econometric methodology of productivity analysis developed here ought to be used as a benchmark to assess productivity effects for other ICAs or surveys with firm-level data of similar characteristics

Central pseudoscalar production in pp scattering and the gluon contribution to the proton spin

Central pseudoscalar production in $pp$ scattering is suppressed at small values of $Q_\perp$, where $Q$ is defined as the difference between the momenta transferred from the two protons. Such a behaviour is expected if the production occurs through the fusion of two vectors. Photon exchange could provide the dominant contribution at low transferred momenta, but we argue that an extension of the experiment could probe the gluon contribution to the proton spin.Comment: 12 pages, 2 figures and 3 tables, uses epsf.sty. Added references and tables. Minor changes include

Assessing the impact of infrastructure quality on firm productivity in Africa : cross-country comparisons based on investment climate surveys from 1999 to 2005

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.Transport Economics Policy&Planning,Economic Theory&Research,E-Business,Labor Policies,Infrastructure Economics

Assessing the impact of infrastructure quality on firm productivity in Africa: Cross-country comparisons based on investment climate surveys from 1999 to 2005

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). We apply microeconometric techniques to investment climate surveys (ICSs) of 26 African countries 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 we evaluated this impact based on 10 different productivity measures. Results are robust once we control for observable fixed effects (red tape, corruption and crime, finance, innovation and labor skills, etc.) obtained from the ICSs. We ranked African countries 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). We divided countries into two blocks: high-incomegrowth 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. We found 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.Africa, Infrastructure, Total factor productivity, Investment climate, Competitiveness,

Investment climate assessment based on demean Olley and Pakes decompositions: methodology and application to Turkey's investment climate survey

Most empirical studies show strong detrimental evidence that regulatory, and administrative, barriers to entry have on productivity and on firm growth. In this paper we evaluate and measure the total factor productivity (TFP) impacts of having; low quality physical infrastructures (electricity, telecommunications, transport, customs, etc.) and bad social infrastructures (rules of law, informality, corruption, etc.). We suggest evaluating the impact on average productivity (TFP) and on the allocative efficiency of production among firms based on several versions of the Olley and Pakes (O&P) decompositions. We evaluate the advantages and disadvantages of each the O&P decomposition in terms of their IC explanatory power. Once we have measured those IC impacts, we compare them with other sources of empirical information obtained from firm’s perceptions on main bottlenecks for firm growth and from doing business reports of the World Bank (2007). For the econometric analysis, we use firm level data bases from Turkey’s manufacturing sector based on Investment Climate surveys (ICs) done by the World Bank. These ICs are done in many other developing countries and therefore we propose to make crosscountry comparisons based on a new demean concept of TFP that also reduces the heterogeneity if using several robust productivity measures within each country

Design and Performance Analysis of an Index Time Frequency Modulation Scheme for Optical Communications

In this article, we propose an index modulation system suitable for optical communications, based on jointly driving the time and frequency of the signal: an index-time frequency hopping (I-TFH) system. We analyze its performance from the point of view of its efficiency in power and spectrum, and its behavior in terms of error probability for the non-turbulent free-space optical (FSO) channel. We compare I-TFH with already proposed index modulated systems of the same nature, but where the amplitude or the number of transmitters are driven instead of the signal frequency. We derive and compare approximations for the average symbol and bit error probabilities of all these systems. The simulation results show that said approximations are tight enough for a wide range of signal-to-noise ratios and system parameters. Moreover, I-TFH shows to be better performing in BER and/or power efficiency than the comparative alternatives, and may offer interesting properties in a variety of contexts.Comment: 13 pages, 10 figures. IEEE Journal of Selected Topics in Signal Processing, 201

Assessing the impact of the investment climate on productivity using firm-level data : methodology and the cases of Guatemala, Honduras, and Nicaragua

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 assessments (ICA) have become a standard instrument for identifying key obstacles to country competitiveness and imputing their impact on productivity, in order to prioritize policy reforms for enhancing competitiveness. Given the survey objectives and the nature and limitations of the data collected, the authors discuss the advantages and disadvantages of using different productivity measures based on data at the firm level. Their main objective is to develop a methodology to appropriately estimate, in a robust manner, the productivity impact of the investment climate variables. To illustrate the use of this methodology, the authors apply it to the data collected for ICAs in three countries-Guatemala, Honduras, and Nicaragua. Observations in logarithms (logs) of the variables, and not in rates of growth, are pooled from all three countries. The econometric analysis is done with variables in logs to reduce the impact of measurement errors and allow inclusion of as many observations as possible since the"panel"data set is very unbalanced. The authors address the endogeneity of the production function inputs and of the investment climate variables by using a variant of the control function approach based on individual firm information, and by aggregating investment climate variables by industry and region. The authors show that it is possible to get robust results for 10 differentproductivity measures, if one follows a consistent econometric methodology of specification and estimation. For policy analysis, they recommend using those results of investment climate variables on productivity that are robust for most of the productivity measures. The also analyze efficiency aspects of firms in each country. Finally, they decompose the results to obtain country-specific impacts and establish corresponding priorities for policy reform. The actual estimates for the three countries show the level of significance of the impact of investment climate variables on productivity. Variables in several categories, red tape and infrastructure in particular, appear to account for over 30 percent of productivity. The policy implications are clear: investment climate matters enormously and the relative impact of the various investment climate variables indicates where reform efforts should be directed. Given the robustness of the results, the authors argue that the econometric methodology of productivity analysis developed here ought to be used as a benchmark to assess productivity effects for other ICAs or surveys with firm-level data of similar characteristics.

Robust investment climate effects on alternative firm-level productivity measures

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.Total factor productivity measures, Investment climate, Observable fixed effects, Robust investment climate elasticities, Input-output elasticities

Robust methodology for investment climate assessment on productivity: application to investment climate surveys from Central America

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 Assessments (ICA) surveys 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 productivity measures. The main objective is to develop a methodology to estimate, in a consistent manner, the productivity impact of the investment climate variables. The paper applies it to the data collected for ICAs in four countries: Costa Rica, Guatemala, Honduras and Nicaragua. Observations on logarithms (logs) of the 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 a variant of the control function approach, based on individual firm information, and by aggregating investment climate variables by industry and region. It is shown that it is possible to get robust results for 10 different productivity measures. The estimates for the four countries show how relevant the investment climate variables are to explain the average level of productivity. 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 indicate where reform efforts should be directed in each country. It is argued that this methodology can be used as a benchmark to assess productivity effects in other ICA surveys. This is important because ICA surveys are available now for more than 65 developing countries.Total factor productivity, Investment climate, Competitiveness, Firm level determinants of productivity, Robust productivity impacts,