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"This study measures the impact of investment climate factors on total factor productivity (TFP) of firms in Brazil and China. The analysis is conducted in two steps: first an econometric production function is estimated to produce a measure of TFP at the firm level. In the second step, variation in TFP across firms is statistically related to a indicators of the investment climate as well as firm characteristics. The results yield a number of insights about the factors underlying productivity. In both countries, and in a variety of industry groups, indicators of poor investment climate, especially delays in customs clearance and interruptions in utility services, have significant negative effects on TFP. Reducing customs clearance time by one day in China could increase TFP by 2-6 percent. Indicators such as email usage have positive effects on TFP. In the case of China, state-owned firms and firms located in the interior are shown to be much less productive than privately owned firms and firms located in the east. In Brazil, the results present an interesting contrast between the apparel industry and the electronics industry. In the apparel industry, older firms in competitive markets are more productive, while in the case of electronics, newer firms with higher market shares are more productive. "--World Bank web site.

Industrial productivity --- Investments

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Assessments of the economic benefits of transportation infrastructure investments are critical to good policy decisions. At present, most such assessments are based of two types of studies: micro-scale studies in the form of cost-benefit analysis (CBA) and macro-scale studies in the form of national or regional econometric analysis. While the former type takes a partial equilibrium perspective and may therefore miss broader economic benefits, the latter type is too widely focused to provide much guidance concerning specific infrastructure projects or programs. Intermediate (meso-scale) analytical frameworks, which are both specific with respect to the infrastructure improvement in question and comprehensive in terms of the range of economic impacts they represent, are needed. This paper contributes to the development of meso-scale analysis via the specification of a computable general equilibrium (CGE) model that can assess the broad economic impact of improvements in transportation infrastructure networks. The model builds on recent CGE formulations that seek to capture the productivity penalty on firms and the utility penalty on households imposed by congestion (Meyers and Proost, 1997; Conrad, 1997) and others that model congestion via the device of explicit household time budgets (Parry and Bento, 2001, 2002). The centerpiece of our approach is a representation of the process through which markets for non-transport commodities and labor create derived demands for freight, shopping and commuting trips. Congestion, which arises due to a mismatch between the derived demand for trips and infrastructure capacity, is modeled as increased travel time along individual network links. Increased travel time impinges on the time budgets of households and reduces the ability of transportation service firms to provide trips using given levels of inputs. These effects translate into changes in productivity, labor supply, prices and income. A complete algebraic specification of the model is provided, along with details of implementation and a discussion of data resources needed for model calibration and application in policy analysis.

Transport