Economic Modelling最新文献

Empirical economic modelers often have to choose between two classes of models, with each class containing multiple models. In many cases, this decision is based on the predictive ability of the considered models. This entails that multiple testing and/or p-hacking pose known risks. This study presents a new statistical approach for comparing all model in a single test, serving as a multi-benchmark reality check test. The behavior of the test is studied asymptotically and in small finite samples. We show how the new approach works by analyzing whether one family of linear bivariate models outperforms a univariate family in predicting commodity prices. This paper raises new questions for future research. From an empirical viewpoint, we present several open questions in economic modeling that can be tested with multi-benchmark tests. Meanwhile, from a theoretical viewpoint, further studies can investigate whether a more general method for approximating or simulating the test distribution can be developed.

This study examines the effects of carbon pricing in Germany, Spain, and the broader European context using the dynamic, three-region environmental multisector general equilibrium model, EMuSe. Our findings indicate that unilateral carbon pricing in Germany or Spain leads to a sustained negative output. The marginal increase in production costs outweighs modest reductions in emissions. However, when Europe collectively adopts carbon pricing, the long-term output effects become positive, although there are more significant transition costs due to close trade relations within Europe. We find evidence of carbon leakage, which is marginally mitigated by a border adjustment mechanism. However, this mechanism mainly protects domestic carbon-intensive sectors and produces inconsistent country outcomes; Germany gains, while Spain loses. Notably, Spain’s energy sector emerges as a long-term beneficiary due to its relatively lower emission intensity. The findings highlight the strategic importance for Europe to engage global partners in carbon pricing as it reduces the economic downturn phase and increases long-term gains.

Intellectual Property Rights Protection (IPRP) can affect knowledge dissemination and talent flow. However, few studies have examined its effect on regional low-carbon transition and the low-carbon economy. Using carbon emission efficiency (CEE) to measure China's low-carbon transition, we consider the “National Intellectual Property Rights Demonstration Cities” policy as a quasi-experiment and apply a staggered difference-in-differences model to examine IPRP's effect on CEE. We find that IPRP boosts CEE through green innovation and energy intensity and is stronger in coastal, eastern, resourced-based, and big cities. Finally, the significantly positive spillover impact of IPRP boosts CEE in adjacent cities. This study highlights the critical role of the institutional environment in driving low-carbon transitions, offering a foundational framework for developing countries to promote IPRP.

This study examines the impact of industrial robot applications on labor investment efficiency. While previous studies have mainly focused on how industrial robots affect productivity, economic structures, and labor markets, their influence on labor investment efficiency has remained relatively underexplored. Using data from Chinese manufacturing firms, our results demonstrate that the adoption of industrial robots significantly improves labor investment efficiency. This improvement is mainly achieved by optimizing the human capital structure and enhancing capital deepening. We also find that this effect is more pronounced in non-state-owned enterprises, in environments with reduced information asymmetry, and in firms with low R&D investment and labor intensity. Overall, our results highlight the positive effect of industrial robot applications on the efficiency of corporate labor investments from a microeconomic perspective, providing important insights for labor investment decisions and resource allocation optimization.

Several studies have examined specific characteristics of firms while attempting to explain highly skewed firm size distribution and the presence of extreme values. This study adapted the quantal response statistical equilibrium model of boundedly rational firms and used firms’ probabilistic decision-making to infer the equilibrium relative size distribution. The theoretical model complements conventional and entropy-based concentration measures. The study presents an adaptation for business firms in the United States while investigating firms’ expansion decisions, aspired sizes, and responsiveness to opportunities.

A standard endogenous separation model developed by Mortensen and Pissarides (1994) has a drawback in replicating the negative correlation between unemployment and vacancy rates. To address this issue, I extended the model by incorporating wage rigidity and modifying the assumption about idiosyncratic match-specific productivity. Results indicate that introducing wage rigidity can produce the Beveridge curve, while the degree of negative correlation is slightly lower than that presented in the data. Modifying the model to randomly draw match-specific productivity for new matches also increases the degree of negative correlation between unemployment and vacancy rates. These results suggest that an endogenous separation model can explain the observed variation by adding frictions.

Connectedness quantifies the extent of interlinkages within economies or markets based on a network approach. Connectedness is measured by the Diebold–Yilmaz spillover index, and abrupt increases in this measure are thought to result from major events. However, formal statistical evidence of events causing such increases is scant. We develop a bootstrap-based technique to evaluate the probability that the value of the spillover index changes at a statistically significant level following an exogenously defined event. We further show how our procedure can detect the dates of unknown events endogenously. The results of a simulation exercise support the effectiveness of our method. We revisit the original dataset from Diebold and Yilmaz’s seminal work and obtain statistical support that the spillover index increases quickly in the wake of adverse shocks. Our methodology accounts for small sample bias and is robust with respect to modifications of the pre-event period and forecast horizon.

Shocks in housing demand can trigger economic downturns, prompting governments to boost public consumption to mitigate its impact. The literature has found conflicting effects of government spending on residential investment and housing prices. We hypothesize that differences in the construction sector’s responses may be due to factors unaccounted for in the estimations, such as labor supply response to wage changes, labor reallocation between sectors, and the amount of household debt. Using a dynamic general equilibrium model, we demonstrate that government consumption boosts tradable goods production, resulting in increased labor demand and wages. However, this diverts workers away from construction, potentially deepening the wound in this sector. Specific labor market attributes and economic indebtedness can catalyze worker displacement from the construction sector, thus adversely affecting residential investment and overall credit. As a result, borrowers face considerable welfare losses. Redirecting government spending toward housing sustains residential activity while exacerbating the overall welfare decline. Our analysis provides plausible explanations for the disparate empirical evidence on the impact of government spending on the construction sector.

In China's pursuit of digital and green transformation, this study examines the impact of regional digitalization on local firms' green innovation performance. The study develops a theoretical framework based on dynamic capabilities theory to explore how regional digitalization affects green innovation performance of local firms. Employing a quasi-natural experiment involving the National E-commerce Demonstration Cities policy in China, the study conducts empirical analysis using data from listed companies in China during the period 2007–2021. The findings suggest that regional digitalization can increase the quantity and quality of local firms' green innovations by improving their dynamic capabilities, such as sensing, seizing, and reconfiguring. Moreover, the impact of regional digitalization on green innovations is more pronounced in private companies and those with a strong foundation for green transformation. Furthermore, a synergistic effect on green innovations is observed between digitalization policy and its enforcement by local governments. A series of tests, including endogeneity analysis, confirm the robustness of our findings.

The paper examines how fiscal and monetary policy coordination in India stabilizes macroeconomic fundamentals. We consider two coordinating fiscal and monetary policy regimes, the “Indian Fiscal” (IF) and M regime and then examine the transmission of public expenditure (PE) shock across these regimes. Monetary policy in the IFregime supports fiscal policy in debt stabilization by reducing interest rates. The M regime fiscal policy supports monetary policy in curbing inflation through fiscal consolidation drives. The IF regime is more conducive to the Indian economy as PE stimulus accelerates economic activity without causing high inflationary and high debt scenarios. In contrast, the M regime has a crowding out effect on PE stimulus while worsening the government's fiscal space. The findings indicate that in the Indian case, the monetary authority should maintain its accommodative stance on PE stimulus.