Despite substantial research and policy interest in pixel level cropland allocation data, few sources are available that span a large geographic area. The data used for much of this research are ...derived from complex modeling techniques that may include model simulation and other data processing. We develop a transparent econometric framework that uses pixel level biophysical measurements and aggregate cropland statistics to develop pixel level cropland allocation predictions. Such pixel level land use data can be used to investigate the impact of human activities on the environment. Validation exercises show that our approach is effective at downscaling cropland allocation to multiple levels of resolution.
As antibiotic resistance increases and antibiotic development dwindles, new antimicrobial agents are needed. Recent advances in nanoscale engineering have increased interest in metal oxide ...nanoparticles, particularly zinc oxide nanoparticles, as antimicrobial agents. Zinc oxide nanoparticles are promising due to their broad-spectrum antibacterial activity and low production cost. Despite many studies demonstrating the effectiveness of zinc oxide nanoparticles, the antibacterial mechanism is still unknown. Previous work has implicated the role of reactive oxygen species such as hydrogen peroxide, physical damage of the cell envelope, and/or release of toxic Zn 2+ ions as possible mechanisms of action. To evaluate the role of these proposed methods, we assessed the susceptibility of S. aureus mutant strains, Δ katA and Δ mprF , to zinc oxide nanoparticles of approximately 50 nm in size. These assays demonstrated that hydrogen peroxide and electrostatic interactions are not crucial for mediating zinc oxide nanoparticle toxicity. Instead, we found that Zn 2+ accumulates in Mueller-Hinton Broth over time and that removal of Zn 2+ through chelation reverses this toxicity. Furthermore, we found that the physical separation of zinc oxide nanoparticles and bacterial cells using a semi-permeable membrane still allows for growth inhibition. We concluded that soluble Zn 2+ is the primary mechanism by which zinc oxide nanoparticles mediate toxicity in Mueller-Hinton Broth. Future work investigating how factors such as particle morphology (e.g., size, polarity, surface defects) and media contribute to Zn 2+ dissolution could allow for the synthesis of zinc oxide nanoparticles that possess chemical and morphological properties best suited for antibacterial efficacy.
Does education matter for economic growth Delgado, Michael S; Henderson, Daniel J; Parmeter, Christopher F
Oxford bulletin of economics and statistics,
June 2014, Letnik:
76, Številka:
3
Journal Article
Recenzirano
Odprti dostop
Empirical growth regressions typically include mean years of schooling as a proxy for human capital. However, empirical research often finds that the sign and significance of schooling depends on the ...sample of observations or the specification of the model. We use a non‐parametric local‐linear regression estimator and a non‐parametric variable relevance test to conduct a rigorous and systematic search for significance of mean years of schooling by examining five of the most comprehensive schooling databases. Contrary to a few recent articles that have identified significant nonlinearities between education and growth, our results suggest that mean years of schooling is not a statistically relevant variable in growth regressions. However, we do find evidence (within a cross‐sectional framework), that educational achievement, measured by mean test scores, may provide a more reliable measure of human capital than mean years of schooling.
Input- and output-based economic policies designed to reduce water pollution from fertilizer runoff by adjusting management practices are theoretically justified and well-understood. Yet, in ...practice, adjustment in fertilizer application or land allocation may be sluggish. We provide practical guidance for policymakers regarding the relative magnitude and speed of adjustment of input- and output-based policies. Through a dynamic dual model of corn production that takes fertilizer as one of several production inputs, we measure the short- and long-term effects of policies that affect the relative prices of inputs and outputs through the short- and long-term price elasticities of fertilizer application, and also the total time required for different policies to affect fertilizer application through the adjustment rates of capital and land. These estimates allow us to compare input- and output-based policies based on their relative cost-effectiveness. Using data from Indiana and Illinois, we find that input-based policies are more cost-effective than their output-based counterparts in achieving a target reduction in fertilizer application. We show that input- and output-based policies yield adjustment in fertilizer application at the same speed, and that most of the adjustment takes place in the short-term.
•A structural dynamic model is used to quantify policy impacts on fertilizer use.•Input-based policies are more cost-effective to reduce fertilizer use.•Input- and output-based policies yield the same adjustment speed in fertilizer use.•Most of the adjustment in fertilizer use takes place in the short-term.
We investigate heterogeneity between foreign direct investment (FDI) and domestic investment induced by corruption and human capital. Controlling for corruption and human capital, inbound FDI has ...significant, heterogeneous complementarity effects on domestic investment; the effect of outbound FDI on domestic investment is fluid: substitution and complementarity exist, and change direction over time. The fluid effects of outbound FDI oppose the popular dollar-for-dollar hypothesis. Although lower corruption and higher human capital strengthen, weaken, or do not change the degree of these FDI effects, the data are inconsistent with the hypothesis of a global optimum for corruption or human capital. Corruption and human capital do not appear to be binding constraints in all countries. The role of institutional quality appears consistent with the prediction of the General Theory of Second Best.
•FDI from regions other than HK, MC and TW can improve the productivity of the invested firms in China.•FDI from none-HMT regions affects Chinese domestic firms through vertical linkages.•Chinese ...domestic food firms may be crowded out by non-HMT investment in the same industry.•HMT investment can generate positive within-industry productivity spillovers, but negative vertical spillovers.
We investigate the impact of foreign direct investment (FDI) on the total factor productivity of Chinese food firms using firm-level census data between 1998 and 2007 (174,940 sample food firms). We test for within-firm, within-industry, and vertical effects. We find that the effect of FDI on the productivity of Chinese food firms depends significantly on the type of FDI and its countries of origin. FDI from non-HMT (Hong Kong, Macaw and Taiwan) regions can improve the productivity of the invested firm, and also increases the productivity of domestic food firms through vertical industry linkages. However, domestic food firms may be crowded out by non-HMT investment in the same industry. HMT investment can generate positive within-industry productivity spillovers, but negative vertical spillovers. Our findings have immediate implications for policymakers in China, as well as for governments of less developed countries that are formulating foreign investment policies.
We develop a three-step, oracle-efficient estimator for a structural semiparametric smooth coefficient model with endogenous variables in the nonparametric part of the model. We use a control ...function approach, combined with both series and kernel estimators to obtain consistent and asymptotically normal estimators of the functions and their partial derivatives. We develop a residual-based test statistic for testing endogeneity, and demonstrate the finite sample performance of our estimators, as well as our test, via Monte Carlo simulations. Finally, we develop an application of our estimator to the relationship between public benefits and private savings.
Global climate models (GCMs) are important tools for understanding the climate system and how it is projected to evolve under scenario-driven emissions pathways. Their output is widely used in ...climate impacts research for modeling the current and future effects of climate change. However, climate model output remains coarse in relation to the high-resolution climate data needed for climate impacts studies, and it also exhibits biases relative to observational data. Treatment of the distribution tails is a key challenge in existing bias-adjusted and downscaled climate datasets available at a global scale; many of these datasets used quantile mapping techniques that were known to dampen or amplify trends in the tails. In this study, we apply the Quantile Delta Mapping (QDM) method (Cannon et al., 2015) for bias adjustment. After bias adjustment, we apply a new spatial downscaling method called Quantile-Preserving Localized-Analog Downscaling (QPLAD), which is designed to preserve trends in the distribution tails. Both methods are integrated into a transparent and reproducible software pipeline, which we apply to global, daily GCM surface variable outputs (maximum and minimum temperature and total precipitation) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) experiments (O'Neill et al., 2016) for the historical experiment and four future emissions scenarios ranging from aggressive mitigation to no mitigation, namely SSP1–2.6, SSP2–4.5, SSP3–7.0, and SSP5–8.5 (Riahi et al., 2017). We use the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA5 (Hersbach et al., 2020) temperature and precipitation reanalysis as the reference dataset over the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6) reference period of 1995–2014. We produce bias-adjusted and downscaled data over the historical period (1950–2014) and the future emissions pathways (2015–2100) for 25 GCMs in total. The output dataset is the Global Downscaled Projections for Climate Impacts Research (GDPCIR), a global, daily, 0.25∘ horizontal-resolution product which is publicly available and hosted on Microsoft AI for Earth's Planetary Computer (https://planetarycomputer.microsoft.com/dataset/group/cil-gdpcir/, last access: 23 October 2023).
•We propose a semiparametric model that allows corruption to influence the FDI-growth relationship.•We allow for parameter heterogeneity of unknown form and the use of instrumental ...variables.•Corruption has a sizeable nonlinear role in the FDI-growth relationship.•Countries with no or low returns to FDI may benefit substantially from reducing corruption.
Who really wins from foreign direct investment (FDI) and by how much? Should winners care about corruption? Building on evidence of heterogeneity in the FDI-growth relationship, we propose a semiparametric model that allows corruption to influence the relationship between the conditioning variables and GDP growth, parameter heterogeneity of unknown form, and the use of instrumental variables. We find evidence that corruption has a sizeable nonlinear role in the FDI-growth relation, weakening the effectiveness of FDI at improving growth rates in many developing countries. Developing countries with insignificant or low returns to FDI may benefit substantially from reducing corruption.
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