Empirical Economics最新文献

We estimate the effects of monetary policy on the aggregate economy in Japan during the last three decades when the effective lower bound (ELB) on interest rates was occasionally binding. We use monetary policy surprises from the interest rate futures market as the external instrument to identify monetary policy shocks in the vector autoregressive model. We find that monetary policy has been effective in Japan during the last three decades, and the effect was more persistent in the ELB regime than in the non-ELB regime. In a simulation exercise, we further show that a New Keynesian model with forward guidance can replicate our empirical finding.

This paper examines the nature of instability in stochastic dynamical systems. Relying on a quantile approach, we propose to measure dynamic instability by the average rate of divergence ((AR{D}^{text{s}})) of the state along a finite forward stochastic path. Under stochastic shocks, (AR{D}^{text{s}}) is a random variable with a given distribution function that depends on the nature of the underlying dynamic process as well as the nature of the shocks. We show how our approach can be made empirically tractable using a quantile autoregression (QAR) model. In an empirical application to futures price, the QAR estimates provide statistical evidence that futures price instability varies with market conditions: instability increases with the maturity of the futures contract as well as with higher quantiles (representing positive shocks located in the upper tail of the price distribution). We find that neglecting stochastic shocks (e.g., under a deterministic dynamic analysis) tends to overstate the presence of instability. The results stress the importance of evaluating the dynamic impacts of shocks across the whole distribution.

We test whether precious metals and their mining stock counterparts are hedges, diversifiers or safe-havens against equity markets. We resort to multidimensional scaling and wavelet-based quantile correlation method to examine the association between precious metals, indices of precious metal mining stocks and equity market over both quantiles and frequencies. Our results indicate that the white precious metals and the mining stocks of gold and silver are potential diversifier assets. We also find that gold maintains the exclusivity of being both hedge and safe-haven against equity market. The results drawn have important implications for investors and managers operating at different time horizons in the equity market.

This paper provides a comprehensive empirical analysis of the role of discretionary fiscal policy for inflation differentials across the 19 euro area countries over the period 1999–2019. The results confirm existing (older) literature that it is difficult to find robust evidence of the fiscal policy stance or impulse impacting directly on inflation differentials. We do find, however, support for an indirect effect of discretionary fiscal policy on inflation differentials working through the output gap channel. There is also some evidence that fiscal policy may be especially potent in influencing inflation differentials—with fiscal tightening cooling (and fiscal expansion increasing) inflation pressures—when the economy is above its potential. Finally, going from the overall fiscal stance or impulse to individual fiscal instruments, we find that value added tax rate changes and public wage growth are statistically significant determinants of inflation differentials in our sample.

This article introduces a latent class approach to estimate the impact of a continuous and endogenous treatment on a continuous outcome, incorporating observed and unobserved heterogeneity in both the treatment and instrument effects, and relaxing the monotonicity assumption across groups of individuals. Our approach, based on a fully parametric model estimated via maximum likelihood, allows the parameters to vary across different classes (groups) of individuals. Given that the membership of each individual to a given class is unknown, we jointly estimate it alongside class-specific parameters assuming a discrete distribution. We perform a Monte Carlo experiment to evaluate the performance of our estimator under assumptions similar to those of the traditional instrumental variables model. Our results indicate that when the model is well specified, our proposed estimator accurately estimates the true degree of unobserved heterogeneity across classes and the population average treatment effect. We illustrate the practical implementations of our approach with two empirical examples.

This study identifies central bank information shocks and pure monetary policy shocks for Japan by combining high-frequency identification with sign restrictions. The empirical findings provide robust evidence of the central bank information effect in Japan. Specifically, the central bank’s optimistic outlook, conveyed through contractionary monetary actions, reduces economic uncertainty and leads to increases in stock prices and output. Additionally, changes in uncertainty play a significant role in the transmission of the central bank’s information effect. The overall impact of monetary policy and information shocks, as identified through our method, is found to be larger than that identified using conventional techniques such as Cholesky decomposition.

This article analyses how hiring older workers adjusts to demographic change in the labour force by using information from more than 500,000 firms in Germany. We find robust evidence that firms faced with an ageing labour market hire relatively more older workers. However, the pace of this adjustment is relatively slow, particularly when ageing happens outside the firm. The tendency to employ older people is more considerable in East Germany, where the demographic change moves forward faster. Furthermore, part-time working models support hiring older workers, but this effect becomes less important in larger firms and East Germany. Finally, while partial retirement regulations enhance flexibility within the firm, they, unfortunately, diminish the employment opportunities for older external job seekers.

We analyze the impact of COVID-19 diagnoses on student grades, retention, and on-time graduation at a large public university in the USA. Even though COVID-19 rarely causes major health complications for university students, diagnosis and quarantine may cause non-trivial disruptions to learning. Using event study analysis, we find that a COVID-19 diagnosis decreased a student’s term grade point average (GPA) modestly by 0.09 standard deviations in the semester of diagnosis without significant effects afterward. The results were more pronounced for male students, individuals with face-to-face instruction, and those with higher GPAs before the pandemic. We do not find a significant increase in the incidence of failing or withdrawing from a course due to diagnosis. In addition, we find no general evidence that the diagnoses delayed graduation or significantly altered first-year retention. However, the University experienced significant grade inflation during the pandemic, like other institutions, which exceeded the estimated effects of any COVID-19 diagnoses.

The COVID-19 pandemic has triggered an unprecedented shock to global stock markets, exceeding the economic impacts of prior pandemics. This paper examines the pandemic’s impact on global stock markets across 34 countries, focusing on the relationship between the pandemic’s severity, government policy responses, and economic stimuli. Panel data regressions reveal that increased daily COVID-19 cases initially negatively impacted stock returns and increased volatility. Stringent government measures positively influenced market returns but also heightened volatility. The research challenges previous assumptions about the influence of geographical and economic factors on market reactions. By segregating the sample period by investor sentiment, the study finds a consistent pattern of negative lagged returns, indicating stronger mean reversion during high VIX periods. During low market volatility, government stringency measures are perceived as harmful to economic activity, negatively impacting stock returns. The insights from the COVID-19 pandemic can inform responses to future market disruptions from health crises, geopolitical tensions, environmental disasters, or other systemic shocks.

This paper introduces a novel semiparametric econometric framework for policy evaluation and estimates a green knowledge production function for a large, 30-year panel dataset of high-income countries. Due to the substantial uncertainty in the data-generating process and the potential presence of nonlinearities and latent common factors, the paper explores semiparametric panel specifications that go beyond interactive fixed effects fully parametric models. The findings suggest that (i) the semiparametric additive specification with individual time trends is the preferred model, (ii) threshold effects and nonlinearities are salient features of the data that parametric specifications fail to capture, and (iii) the impact of environmental policy is noteworthy and exhibits clear heterogeneity when modelled as a nonparametric function of specific knowledge inputs. The evidence reveals a significant nonlinear policy inducement effect stemming from R&D investments.