Macroeconomic Effects of Credit Deepening in Latin America

This paper augments a relatively standard dynamic general equilibrium model with financial frictions in order to quantify the macroeconomic effects of the credit deepening process observed in many Latin American (LA) countries in the last decade, most notably in Brazil. In the model, a stylized banking sector intermediates credit from patient households to impatient households and firms. The key novelty of the paper, motivated by the Brazilian experience, is to model the credit constraint faced by (impatient) households as a function of future labor income. In the calibrated model, credit deepening generates only modest abovetrend growth in consumption, investment, and GDP. Since Brazil has experienced one of the most intense credit deepening processes in Latin America, it is argued that the quantitative effects for other LA economies are unlikely to be sizeable

Natural-Resource or Market-Seeking FDI in Russia? An Empirical Study of Locational Factors Affecting the Regional Distribution of FDI Entries

This paper conducts an empirical study of the factors that affect the spatial distribution of foreign direct investment (FDI) across regions in Russia; in particular, this paper is concerned with those regions that are endowed with natural resources and marketrelated benefits. Our analysis employs data on Russian firms with a foreign investor during the 2000-2009 period and linked regional statistics in the conditional logit model. The main findings are threefold. First, we conclude that one theory alone is not able to explain the geographical pattern of foreign investments in Russia. A combination of determinants is at work; market-related factors and the availability of natural resources are important factors in attracting FDI. The relative importance of natural resources seems to grow over time, despite shocks associated with events such as the Yukos trial. Second, existing agglomeration economies encourage foreign investors by means of forces generated simultaneously by sector-specific and inter-sectoral externalities. Third, the findings imply that service-oriented FDI co-locates with extraction industries in resource-endowed regions. The results are robust when Moscow is excluded and for subsamples including only Greenfield investments or both Greenfield investments and mergers and acquisitions (M&A).Dieses Arbeitspapier ist eine empirische Studie der Faktoren, die auf den räumlichen Verteilungsprozess von Auslandsdirektinvestitionen (FDI) in den russischen Regionen wirken. Insbesondere befasst sich die Studie dabei mit den Regionen, die mit natürlichen Ressourcen und umfassenden Märkten ausgestattet sind. In unserer Analyse kombinieren wir umfangreiche Regionaldaten mit Firmendaten russischer Unternehmen, in die mindestens ein ausländischer Investor im Zeitraum zwischen 2000 und 2009 investiert hat. Die Analyse nach den Standortfaktoren wird in einem Conditional Logit Modell untersucht. Die grundlegenden Ergebnisse der Studie sind dreifach zu differenzieren. Erstens kann festgestellt werden, dass eine Theorie alleine nicht ausreicht, um das geographische Muster von FDI in Russland zu erklären. Vielmehr kann eine Kombination der Determinanten festgestellt werden; marktbedingte Faktoren und die Zugänglichkeit von natürlichen Ressourcen stellen sich als wichtige Komponenten für die Ansiedlung ausländischer Investoren dar. Der Einfluss natürlicher Ressourcen ist dabei stetig über die Zeit gewachsen, ungeachtet von exogenen Schocks wie beispielsweise dem Yukos-Prozess. Zweitens wirken Agglomerationseffekte auf die Standwortwahl ausländischer Investoren sowohl durch sektorspezifische als auch durch intersektorale Externalitäten. Drittens zeigen die Ergebnisse, dass der Zugang zu natürlichen Ressourcen FDI in Dienstleistungssektoren nach sich zieht. Auch wenn Investitionen in Moskau ausgegrenzt bzw. M&A (Mergers & Acquistions) Investitionen hinzugenommen werden, bleiben die Regressionsergebnisse stabil

Is There Surplus Labor in Rural India?

We show empirically using panel data at the plot and farm level and based on a model incorporating supervision costs, risk, credit-market imperfections and scale-economies associated with mechanization that small-scale farming is inefficient in India. Larger farms are more profitable per acre, more mechanized, less constrained in input use after bad shocks, and employ less per-acre labor than small farms. Based on our structural estimates of the effects of farm size on labor use and the distribution of Indian landholdings, we estimate that over 20% of the Indian agricultural labor force is surplus if minimum farm scale is 20 acres