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

Dynamic Bayesian smooth transition autoregressive models applied to hourly electricity load in southern Brazil

Dynamic Bayesian Smooth Transition Autoregressive (DBSTAR) models are proposed for nonlinear autoregressive time series processes as alternative to both the classical Smooth Transition Autoregressive (STAR) models of Chan and Tong (1986) and the Bayesian Simulation STAR (BSTAR) models of Lopes and Salazar (2005). Unlike those, DBSTAR models are sequential polynomial dynamic analytical models suitable for inherently non-stationary time series with non-linear characteristics such as asymmetric cycles. As they are analytical, they also avoid potential computational problems associated with BSTAR models and allow fast sequential estimation of parameters. Two types of DBSTAR models are defined here based on the method adopted to approximate the transition function of their autoregressive components, namely the Taylor and the B-splines DBSTAR models. A harmonic version of those models, that accounted for the cyclical component explicitly in a flexible yet parsimonious way, were applied to the well-known series of annual Canadian lynx trappings and showed improved fitting when compared to both the classical STAR and the BSTAR models. Another application to a long series of hourly electricity loading in southern Brazil, covering the period of the South-African Football World Cup in June 2010, illustrates the short-term forecasting accuracy of fast computing harmonic DBSTAR models that account for various characteristics such as periodic behaviour (both within-the-day and within-the-week) and average temperature

Modulation of attosecond beating in resonant two-photon ionization

We present a theoretical study of the photoelectron attosecond beating at the basis of RABBIT (Reconstruction of Attosecond Beating By Interference of Two-photon transitions) in the presence of autoionizing states. We show that, as a harmonic traverses a resonance, its sidebands exhibit a peaked phase shift as well as a modulation of the beating frequency itself. Furthermore, the beating between two resonant paths persists even when the pump and the probe pulses do not overlap, thus providing a sensitive non-holographic interferometric means to reconstruct coherent metastable wave packets. We characterize these phenomena quantitatively with a general finite-pulse analytical model that accounts for the effect of both intermediate and final resonances on two-photon processes, at a negligible computational cost. The model predictions are in excellent agreement with those of accurate ab initio calculations for the helium atom in the region of the N=2 doubly excited states

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

Investment climate and firm’s economic performance: econometric methodology and application to Turkey's investment climate survey

Government policies and behavior exert a strong influence on the investment climate through their impact on costs, risks and barriers to competition. Key factors affecting the investment climate through their impact on costs are: corruption, taxes, the regulatory burden and extent of red tape in general, factor markets (labor, intermediate materials and capital), the quality of infrastructure, technological and innovation support, and the availability and cost of finance. While the investment climate surveys are quite useful in identifying major issues and bottlenecks as perceived by firms, the data collected is also meant to provide the basic information for an econometric assessment of the impact or contribution of the investment climate (IC) variables on productivity. We believe that improving the investment climate (IC) is a key policy instrument to promote economic growth and to mitigate the institutional, legal, economic and social factors that are constraining the convergence of per capita income and labor productivity of Turkey relative to more developed countries. For that, we need to identify the main investment climate variables that affect economic performance measures like total factor productivity, employment, wages, exports and foreign direct investment and this is the main goal of this paper. In turn, that quantified impact is used in the advocacy for, and design of, investment-climate reforms