Explore the vast range of titles available.

Propensity score matching estimators (Rosenbaum and Rubin (1983)) are widely used in evaluation research to estimate average treatment effects. In this article, we derive the large sample distribution of propensity score matching estimators. Our derivations take into account that the propensity score is itself estimated in a first step, prior to matching. We prove that first step estimation of the propensity score affects the large sample distribution of propensity score matching estimators, and derive adjustments to the large sample variances of propensity score matching estimators of the average treatment effect (ATE) and the average treatment effect on the treated (ATET). The adjustment for the ATE estimator is negative (or zero in some special cases), implying that matching on the estimated propensity score is more efficient than matching on the true propensity score in large samples. However, for the ATET estimator, the sign of the adjustment term depends on the data generating process, and ignoring the estimation error in the propensity score may lead to confidence intervals that are either too large or too small.

Despite lower incomes, the self-employed consistently report higher satisfaction with their jobs. But are self-employed individuals also happier, more satisfied with their lives as a whole? High job satisfaction might cause them to neglect other important domains of life, such that the fulfilling job crowds out other pleasures, leaving the individual on the whole not happier than others. Moreover, selfemployment is often chosen to escape unemployment, not for the associated autonomy that seems to account for the high job satisfaction. We apply matching estimators that allow us to better take into account the above-mentioned considerations and construct an appropriate control group (in terms of balanced covariates). Using the BHPS dataset that comprises a large nationally representative sample of the British populace, we find that individuals who move from regular employment into self-employment experience an increase in life satisfaction (up to 2 years later), while individuals moving from unemployment to self-employment are not more satisfied than their counterparts moving from unemployment to regular employment. We argue that these groups correspond to \"opportunity\" and \"necessity\" entrepreneurship, respectively. These findings are robust with regard to different measures of subjective well-being as well as choice of matching variables, and also robustness exercises involving \"simulated confounders\".

Traditional retailers are closing down their brick and mortar stores and increasing investments in their online channels. This may not be a beneficial strategy for retailers selling nondigital products, such as apparel, which customers prefer to physically evaluate to make the purchase decision. In such product categories, retailers’ physical stores could influence the sales on its online channel. We utilize the event of store opening by a large apparel retailer and use customer-level data to examine the effect of store presence on the online purchase behavior of its existing customers. We find that the retailer’s store openings resulted in an increase in online purchases from such customers for two reasons. First, higher store interactions engaged customers with the retailer’s brand, which resulted in their higher online purchases. Second, customers could freely purchase apparel from the retailer’s online channel, because they had the option to return it at a nearby store if it did not fit their expectations. Multichannel retailers should organize store events to engage customers and design lenient return policies to reduce the risk of purchase from online channel. We utilize the event of store opening by a large apparel retailer and use customer-level data to estimate the effect of store presence on the online purchase behavior of its existing customers. We find that the retailer’s store openings resulted in an increase in online purchases from such customers. Drawing on the theory of planned behavior and prospect theory, we propose two mechanisms to explain this complementary effect of store presence on online purchases by existing customers. These mechanisms are the store engagement effect —customers making higher online purchases because of higher engagement from store interactions—and the store return effect —reduced risk of online purchase because of the option of store returns. We provide direct empirical evidence of these mechanisms on customer-level data. We further show that these effects increase as customers’ distances from the retailer’s store reduce because of the store openings. Our findings have significant implications for multichannel retailers. The online appendices are available at https://doi.org/10.1287/isre.2018.0814 .

Matching estimators for average treatment effects are widely used in evaluation research despite the fact that their large sample properties have not been established in many cases. The absence of formal results in this area may be partly due to the fact that standard asymptotic expansions do not apply to matching estimators with a fixed number of matches because such estimators are highly nonsmooth functionals of the data. In this article we develop new methods for analyzing the large sample properties of matching estimators and establish a number of new results. We focus on matching with replacement with a fixed number of matches. First, we show that matching estimators are not N1/2-consistent in general and describe conditions under which matching estimators do attain N1/2-consistency. Second, we show that even in settings where matching estimators are N1/2-consistent, simple matching estimators with a fixed number of matches do not attain the semiparametric efficiency bound. Third, we provide a consistent estimator for the large sample variance that does not require consistent nonparametric estimation of unknown functions. Software for implementing these methods is available in Matlab, Stata, and R.

One of the most pressing socio-economic issues across EU countries has been the depopulation of a significant part of its territory. Less urbanized areas are perceived as non-attractive places to live and have been losing population steadily in the latest decades. For the case of Spain, this European-wise phenomenon has been exacerbated for several territories characterized by a large presence of primary and extractive industries in the past. We quantify empirically the contribution that the closure of the heavily subsidized coal mining had on the depopulation trends experienced in mining-intensive areas in Spain. This poses an interesting research question, since both non-mining and mining territories in Spain suffered a remarkable negative down trend in demographic terms since early nineties, which was the period on which the coal mining industry started to cease steadily its activity. Our empirical strategy relies on matching estimators that compare the demographic trend across mining-intensive and non-mining intensive municipalities in four provinces, controlling for observable characteristics and isolating the net effect of the “shock” originated by the termination of this mining activities. Our analysis finds a statistically significant and sizable negative effect on the fall of population for mining-intensive municipalities between 1991 and 2011.

Cover crops can generate both on-farm and water-quality benefits. However, their use in Iowa remains subdued, partly due to implementation costs faced by farmers. We tested the hypothesis that monetary incentives through cost-share programs are effective at increasing the area of farmland planted to cover crops in Iowa, as opposed to the alternative in which the participants of cost-share programs would have planted the same cover-crop acreage in the absence of payment. We found that cost-share payments induced a 15 percentage-point expansion in cover-crop acreage beyond what would have been planted in the absence of payment, among farmers who participated in cost-share programs. The estimated additionality rate was 54%, suggesting at least half of cost-share expenditures funded cover-crop acreage that would not have been planted without payment. Furthermore, we estimated the public cost to reduce nitrogen loads to Iowa waterways via cover crop, beyond what would have occurred in the absence of cost-share programs, to be$1.72–$ 4.70 lb −1 N ( $3.79–$ 10.36 kg −1 N). Farmers absorbed about 70% of those costs as private losses, and cost-share payments offset the remaining 30%. Although the additionality rate estimated in this study is less than what has been found in other states, the cost-share programs in Iowa have been relatively cost-effective, due to their lower payment rate.

It is well-known in the literature that self-employment positively influences job satisfaction, but the effects on other life domains and overall life satisfaction are much less clear. Our study analyzes the welfare effects of self-employment apart from its monetary aspects, and focuses on the overall life satisfaction as well as different domain satisfactions of self-employed individuals in our German sample from 1997 to 2010. Using matching estimators to create an appropriate control group and differentiating between different types of self-employment, we find that voluntary self-employment brings with it positive benefits apart from work satisfaction, and leads to higher overall life satisfaction as well as increased health satisfaction, all of which increase in the first three years of self-employment. Being forced into self-employment to escape unemployment, however, confers no such benefits. Additionally, both types of self-employment lead to increasing dissatisfaction with one’s leisure time.

Inactive individuals represent a pool of potential labour whose activation entails economic and social advantages. Additionally, being active allows individuals to cover their basic psychological needs—autonomy, competence and relatedness—which leads to greater satisfaction through self-determination. We posit that self-employment may be an attractive alternative because its nonpecuniary aspects may suit their needs better. Using data from the European Community Household Panel, we applied propensity score matching techniques to analyse the change in satisfaction with main activity of inactive individuals becoming self-employed compared to those becoming employees and those remaining inactive. We further perform separate analyses for homemakers, retirees and students to account for heterogeneity within inactivity. We find that self-employment is associated with more satisfaction than remaining inactive in the case of retirees and homemakers, while students tend to experience a larger increase in satisfaction when entering self-employment compared to paid employment. The implications of these results for activation and entrepreneurship policies are discussed.

Background As global ageing continues to increase and many countries face challenges from the growing demand for long-term care. Drawing on the experiences of developed countries, developing countries have explored their own suitable long-term care insurance and have shown strong potential for development and research prospects. However, due to their late start, relevant research is underrepresented in the global research network and still needs to be supplemented. The present study hopes to examine the effect of long-term care insurance on healthcare utilization among the middle-aged and elderly from an empirical perspective, using China as an example. Methods Panel data from wave 3 (2015) and wave 4 (2018) of the nationally-representative China health and retirement longitudinal study were selected to obtain a sample of 661 processing participants and 16,065 control participants after matching the policy implementation time in the first pilot cities, and quantitative analysis was conducted using difference-in-differences propensity score matching estimator method to assess the net effect of long-term care insurance on health care utilization among the middle-aged and elderly adults. Results In the matched frequency-weighted regression difference-in-differences estimator results, long-term care insurance had a negative effect on the number and costs of annual hospitalizations at the 5% significance level (key variable values of − 0.0568101 and − 1236.309, respectively) and a non-significant effect on outpatient service utilization ( P  > 0.05). Further exploration of the heterogeneous effect of it revealed that implementation had a more significant negative effect on hospitalization utilization for middle-aged and older people in the East and for those with higher levels of education or attended care. Conclusion Long-term care insurance has played a role in controlling hospitalization costs but has not yet achieved the expected effect in controlling outpatient costs. The policy effects in terms of regional distribution and education level and care situation have been variable. The treatment plan of long-term care insurance needs to be improved, the supply of resources for long-term care services should be increased, and the promotion of long-term care insurance and health science should be given attention.

The Jeffreys divergence is a renown arithmetic symmetrization of the oriented Kullback–Leibler divergence broadly used in information sciences. Since the Jeffreys divergence between Gaussian mixture models is not available in closed-form, various techniques with advantages and disadvantages have been proposed in the literature to either estimate, approximate, or lower and upper bound this divergence. In this paper, we propose a simple yet fast heuristic to approximate the Jeffreys divergence between two univariate Gaussian mixtures with arbitrary number of components. Our heuristic relies on converting the mixtures into pairs of dually parameterized probability densities belonging to an exponential-polynomial family. To measure with a closed-form formula the goodness of fit between a Gaussian mixture and an exponential-polynomial density approximating it, we generalize the Hyvärinen divergence to α-Hyvärinen divergences. In particular, the 2-Hyvärinen divergence allows us to perform model selection by choosing the order of the exponential-polynomial densities used to approximate the mixtures. We experimentally demonstrate that our heuristic to approximate the Jeffreys divergence between mixtures improves over the computational time of stochastic Monte Carlo estimations by several orders of magnitude while approximating the Jeffreys divergence reasonably well, especially when the mixtures have a very small number of modes.