Oxford Bulletin of Economics and Statistics最新文献

This study investigates different cognitive and non-cognitive characteristics associated with individuals' willingness to get vaccinated against Covid-19 and their actual vaccination status. Our empirical analysis is based on data obtained from three survey waves conducted in 2021 among about 2,000 individuals living in the German state of North Rhine-Westphalia. We find that individuals with a high level of trait reactance – a personality characteristic that entails the personal tendency to perceive persuasion attempts as restricting one's freedom – display a significantly lower willingness to get vaccinated. They also tend to get inoculated later or never. Moreover, neuroticism, locus of control, and statistical numeracy appear to be associated with the willingness to get vaccinated, but these results are less pronounced and less robust. Our results indicate that vaccination campaigns and policies could be improved by specifically addressing those with a high level of trait reactance.

The provision of healthcare in the United States is increasingly reliant on immigrant workers. In this paper, I examine the impact of Secure Communities, a major immigration enforcement program designed to check the immigration status of all individuals arrested by local police, on staffing levels in nursing homes. Using a difference-in-differences strategy that exploits the staggered activation of Secure Communities across US counties, I found that the program reduced directcare staff hours per resident day by 0.073, an approximately 2% decline relative to the mean of treatment counties in the baseline period. This finding suggests that stringent immigration enforcement may exacerbate the healthcare worker shortage in the United States.

‘Zombie lending’ occurs when a lender supports an otherwise insolvent borrower. Recent studies document that zombie lending has been widespread following the European sovereign debt crisis. In this paper, I develop a quantitative model to study the impact of these lending practices on firm dynamics. In the model, firm liquidations and zombie lending arise endogenously. The model provides a good match to key euro-area firm statistics over the period 2011–14. I find that zombie lending has a substantial impact on borrowing costs, helping more low-productivity firms to survive. This, in turn, causes a drag on aggregate output, investment and productivity.

This paper analyzes the export volatility sources estimating a dynamic factor model on transaction-level data. Utilizing an exhaustive dataset of French export transactions from 1993 to 2017, we reconstruct the latent factors space associated with global and destination-specific macroeconomic shocks through a Quasi-Maximum likelihood approach which allows accommodating both the high share of missing values and the high dimensionality of the microeconomic time series. The estimated parameters are then used to derive a volatility decomposition of the aggregate and firm-level export growth rates, highlighting structural spatial patterns and the role of geographical diversification in mitigating export risks.

I provide new empirical estimates of the effect of state capacity on economic development across countries over the period 1960–2022. Specifically, I construct a comprehensive state capacity index based on six different dimensions of effective state institutions available in the Varieties of Democracy (V-Dem) dataset. Then, I estimate heterogeneous parameter models under a common factor framework. My empirical strategy explicitly allows the growth effect of state capacity to differ across countries and accounts for unobserved common factors. My preferred estimates indicate that a one-standard-deviation increase in the V-Dem-based state capacity index predicts a rise in income per person by roughly 6%–7%. The magnitude of such impact equates to less than half of that implied by conventional estimates obtained under highly restrictive assumptions of slope homogeneity and cross-sectional independence. Furthermore, I provide partial evidence suggesting that worldwide heterogeneity in the economic importance of state capacity is deeply rooted in prehistorically determined population diversity, state history, long-term relatedness between countries, and interpersonal trust.

The determinants of an economy's growth path for income per head may vary over time. In this paper, we apply unobserved components analysis to an otherwise standard panel model of economic growth dynamics so that an economy's long-run relative income per head can change at any point of time. We apply this model to data for US states for 1929–2021 and the world economy for 1970–2019. In both datasets an economy's initial relative income per head is a good predictor of its long-run relative income per head. Relatively poor economies on average remain relatively poor.

Many European countries introduced austerity policies to control rising debt in the wake of the Great Recession of the late 2000s. Recent research suggests that austerity fuelled political polarization, instability, and populism in Europe. However, the motives behind citizens' responses to austerity are not well understood. Using the case of the UK, we study whether preferences for redistribution drive the effect of austerity on political participation in the form of voting, appealing for reform with the government, and protesting. Based on experimental and observational data, we show that individual exposure to austerity increases voting and appealing for reform with the government but not protesting, and changes people's preferences for redistribution. The experimental data show that being exposed to austerity is associated with a 0.128 and a 0.096 unit increase in voting and appealing for reform, respectively. The data also show that exposure to austerity increases preferences for taxing higher incomes and spending more on welfare and social security. This change in preferences explains between 8% and 11% of the effect of exposure to austerity on political participation.

Technological change has been biased towards replacing routine labour over the past four decades. We study the implications of those shifts in the task composition of labour demand on hours worked fluctuations. We build quarterly time series on hours worked and task premiums from the CPS and assess the effects of routine-biased technological change by estimating a VAR model with long-run exclusion and sign restrictions. The results indicate that the decline in total hours worked is driven by routine-biased technology shocks through a decline in routine hours. These shocks generate recognizable aggregate fluctuations pointing out to their potential relevance for business cycles.

In hierarchical prior longitudinal models, random effects are estimated by the Gibbs sampler. We show that fixed effects can be handled by a similar Gibbs sampler under a diffuse prior on the unobserved heterogeneity. The dummy variable approach for fixed effects is computationally intensive and has the out-of-memory risk, while the Gibbs sampler can reproduce the dummy variable estimator without creating dummy variables, and therefore avoids the memory burden. Compared to alternating projections and other classical approaches, our method simplifies both inference and estimation of the limited dependent variable models with fixed effects. The proposed method is applied to a real-world mortgage dataset for classification with three-way fixed effects on banks, regions, and loan purposes.