Suchergebnisse

Although there is considerable evidence on the link between foreign direct investment (FDI) and economic growth in developing countries, causal patterns of the two variables has not been investigated yet with a reliable procedure. This article provides an empirical assessment of the issue by using data for 11 economies in East Asia and Latin America. Although FDI is expected to boost host economic growth, it is shown that the extent to which FDI is growth‐enhancing appears to depend on country‐specific characteristics. Particularly, FDI tends to be more likely to promote economic growth when host countries adopt liberalized trade regime, improve education and thereby human capital conditions, encourage export‐oriented FDI, and maintain macroeconomic stability.

While the United States is the largest source of foreign direct investment (FDI) in the world, and China is the largest FDI recipient among developing countries, U.S. direct investment (USDI) in China has been surprisingly small. This article investigates the determinants of USDI through a relative‐demand model with time‐series data. Evidence presented in this article indicates that the small USDI cannot be fully appreciated without understanding differences between USDI and Hong Kong direct investment (HKDI), the latter being the dominant source of FDI in China. Empirical results suggest that the USDI in China was primarily motivated by market access and that the HKDI was export oriented. The small USDI thus is a result of U.S. investors' preference for market access and China's export‐promotion FDI regime, along with the troubled Sino‐U.S. relations and political instabilities in China.

The Thirty years since China's reform and opening have been very eventful for the country in in the areas of sexual and reproductive health, and this volume presents a multi-disciplinary look at the current scholarship going on in China on the subject, translated into English to assist scholars worldwide in understanding China's recent history.

Institutional disincentives often discourage major actors, such as politicians, corporate leaders, and the public, from taking practical steps to protect the environment in China. By using the crackdown on crime in the Chinese megacity of Chongqing as a case study, we argue that despite the strength of these disincentives, they are nevertheless highly susceptible to changes in the macro political environment, which can temporarily alter the regular preference order of these major political-economic actors and reduce industrial pollution. We employed the difference-in-differences approach and observed that the quality of surface water in Chongqing improved during the anticrime campaign because of reduced industrial wastewater discharge. However, after the campaign, the political atmosphere relaxed and the surface water quality declined. These findings suggest that reforming the institutions that shape the incentives of the major actors in environmental protection is critical to improving environmental protection in the long term. ; postprint

Elections affect the division of resources in society and are occasions for political elites to make appeals rooted in voters' self-interest. Hence, elections may erode altruistic norms and cause people to behave more selfishly. We test this intuition using Dictator Games in a lab-in-the-field experiment involving a sample of more than 1000 individuals in Kenya and Tanzania. We adopt two approaches. First, we experimentally prime participants to think about the upcoming or most recent elections and find that this priming treatment reduces how much money participants are willing to give to other players. Second, we compare results obtained across lab rounds in Kenya taking place right before the country's 2013 national elections and eight months prior, and find that selfishness is greater in the lab round more proximate to the election. Our results suggest that elections may affect social behavior in important—and previously unrecognized—ways.

Elections affect the division of resources in society and are occasions for political elites to make appeals rooted in voters' self-interest. Hence, elections may erode altruistic norms and cause people to behave more selfishly. We test this intuition using Dictator Games in a lab-in-the-field experiment involving a sample of more than 1000 individuals in Kenya and Tanzania. We adopt two approaches. First, we experimentally prime participants to think about the upcoming or most recent elections and find that this priming treatment reduces how much money participants are willing to give to other players. Second, we compare results obtained across lab rounds in Kenya taking place right before the country's 2013 national elections and eight months prior, and find that selfishness is greater in the lab round more proximate to the election. Our results suggest that elections may affect social behavior in important—and previously unrecognized—ways.

Ethnicity has been shown to shape political, social, and economic behavior in Africa, but the underlying mechanisms remain contested. We utilize lab experiments to isolate one mechanism - an individual's bias in favor of coethnics and against non-coethnics - that has been central in both theory and in the conventional wisdom about the impact of ethnicity. We employ an unusually rich research design involving a large sample of 1300 participants from Nairobi, Kenya; the collection of multiple rounds of experimental data with varying proximity to national elections; within-lab priming conditions; both standard and novel experimental measures of coethnic bias; and an implicit association test (IAT). We find very little evidence of an ethnic bias in the behavioral games, which runs against the common presumption of extensive coethnic bias among ordinary Africans and suggests that mechanisms other than a coethnic bias in preferences must account for the associations we see in the region between ethnicity and political, social, and economic outcomes.

Ethnic divisions have been shown to adversely affect economic performance and political stability, especially in Africa, but the underlying reasons remain contested, with multiple mechanisms potentially playing a role. We utilize lab experiments to isolate the role of one such mechanism — ethnic preferences — which have been central in both theory and in the conventional wisdom about the impact of ethnic differences. We employ an unusually rich research design, collecting multiple rounds of experimental data with a large sample of 1,300 subjects in Nairobi; employing within-lab priming conditions; and utilizing both standard and novel experimental measures, including implicit association tests. The econometric approach was pre-specified in a registered pre-analysis plan. Most of our tests yield no evidence of coethnic bias. The results run strongly against the common presumption of extensive ethnic bias among ordinary Kenyans, and suggest that other mechanisms may be more important in explaining the negative association between ethnic diversity and economic and political outcomes.

On-road vehicle emissions are a major contributor to elevated air pollution levels in populous metropolitan areas. We developed a link-level emissions inventory of vehicular pollutants, called EMBEV-Link (Link-level Emission factor Model for the BEijing Vehicle fleet), based on multiple datasets extracted from the extensive road traffic monitoring network that covers the entire municipality of Beijing, China (16 400 km 2 ). We employed the EMBEV-Link model under various traffic scenarios to capture the significant variability in vehicle emissions, temporally and spatially, due to the real-world traffic dynamics and the traffic restrictions implemented by the local government. The results revealed high carbon monoxide (CO) and total hydrocarbon (THC) emissions in the urban area (i.e., within the Fifth Ring Road) and during rush hours, both associated with the passenger vehicle traffic. By contrast, considerable fractions of nitrogen oxides ( NO x ), fine particulate matter (PM 2.5 ) and black carbon (BC) emissions were present beyond the urban area, as heavy-duty trucks (HDTs) were not allowed to drive through the urban area during daytime. The EMBEV-Link model indicates that nonlocal HDTs could account for 29 % and 38 % of estimated total on-road emissions of NO x and PM 2.5 , which were ignored in previous conventional emission inventories. We further combined the EMBEV-Link emission inventory and a computationally efficient dispersion model, RapidAir ® , to simulate vehicular NO x concentrations at fine resolutions (10 m × 10 m in the entire municipality and 1 m × 1 m in the hotspots). The simulated results indicated a close agreement with ground observations and captured sharp concentration gradients from line sources to ambient areas. During the nighttime when the HDT traffic restrictions are lifted, HDTs could be responsible for approximately 10 µ g m −3 of NO x in the urban area. The uncertainties of conventional top-down allocation methods, which were widely used to enhance the spatial resolution of vehicle emissions, are also discussed by comparison with the EMBEV-Link emission inventory.