This paper presents a meta-analysis of the literature on multinational companies and productivity spillovers. By collecting information from a sample of published and unpublished papers on the impact of multinational presence on domestic productivity, we investigate whether certain aspects of the study design affect the results, and whether there is publication bias in the literature. Our ®ndings show that some aspects of the empirical methods used, namely, how the presence of multinationals is de®ned, and whether cross-section or panel analysis is employed, may have an effect on the results. We also discover some evidence that there may be publication bias.

We investigate the role that climatic change has played in the pattern of urbanization in sub-Saharan African countries compared to the rest of the developing world. To this end we assemble a cross-country panel data set that allows us to estimate the determinants of urbanization. The results of our econometric analysis suggest that climatic change, as proxied by rainfall, has acted to change urbanization in sub-Saharan Africa but not elsewhere in the developing world. Moreover, this link has become stronger since decolonization, which is likely due to the often simultaneous lifting of legislation prohibiting the free internal movement of native Africans.

We investigate the impact of international outsourcing on productivity using plant level data for Irish manufacturing. Specifically, we distinguish the effect of outsourcing of materials from services inputs. Moreover, we examine whether the impact on productivity is different for plants being more embedded in international markets through exporting or being part of a multinational. Our results show that productivity benefits only accrue to affiliates of foreignowned multinationals and exporters. In particular, for foreign-owned exporting plants increased international outsourcing of both services and materials is associated with higher productivity, whereas this link only exists for domestic exporters' outsourcing of materials.

We estimate for the first time the impact of hurricane strikes on local economic growth rates and how this is reflected in more aggregate growth patterns. To this end we assemble a panel data set of US coastal counties' growth rates and construct a novel hurricane destruction index that is based on a monetary loss equation, local wind speed estimates derived from a physical wind field model, and local exposure characteristics. Our econometric results suggest that in response to a hurricane strike a county's annual economic growth rate will initially fall by 0.8, but then partially recover by 0.2 percentage points. While the pattern is qualitatively similar at the state level, the net effect over the long term is negligible. Hurricane strikes do not appear to be economically important enough to be reflected in national economic growth rates.

Abstract-What determines human beings' political preferences? Using nationally representative longitudinal data, we show that having daughters makes people more likely to vote for left-wing political parties. Having sons leads people to favor right-wing parties. The paper checks that our result is not an artifact of family stopping rules, discusses the predictions from a simple economic model, and tests for possible reverse causality.

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We examine the importance of a firm's own R&D activity and intra-sectoral spillovers on the decision to export and the export intensity using firm level panel data for Spain for the period 1990-98. Own R&D activity is found to be an important determinant of export activity. There is little evidence to suggest that Spanish firms benefit from spillovers of the exporting activity of others. However, there is evidence that R&D spillovers exert positive effects on firms' export ratios. We find a larger marginal impact of R&D spillovers on export intensity of firms exporting to other OECD countries than those exporting to non-OECD nations.

In light of the existing preliminary evidence of a link between Covid-19 and poor air quality, which is largely based upon correlations, we estimate the relationship between long term air pollution exposure and Covid-19 in 355 municipalities in the Netherlands. Using detailed data we find compelling evidence of a positive relationship between air pollution, and particularly PM 2.5 concentrations, and Covid-19 cases, hospital admissions and deaths. This relationship persists even after controlling for a wide range of explanatory variables. Our results indicate that, other things being equal, a municipality with 1 μg/m 3 more PM 2.5 concentrations will have 9.4 more Covid-19 cases, 3.0 more hospital admissions, and 2.3 more deaths. This relationship between Covid-19 and air pollution withstands a number of sensitivity and robustness exercises including instrumenting pollution to mitigate potential endogeneity in the measurement of pollution and modelling spatial spillovers using spatial econometric techniques.