Exploiting the executive compensation reform for state-owned enterprises (SOEs) in China that enforce strict pay restrictions, this study examines whether and how pay restrictions affect firms’ labor investment inefficiency. We find that SOEs experience a decrease in abnormal labor investment following the reform relative to non-SOEs, particularly in over-investment in labor. Our results show that the reform is associated with lower labor investment inefficiency through strengthened internal governance and mitigated internal social comparison. In addition, pay restrictions specifically curb firms’ tendency to over-hire. Further analysis reveals that imposing pay restrictions on executives enhances labor quality and also promotes employee well-being. This study offers novel policy insights by showing how pay restrictions to SOE executives can reduce vertical agency costs and investment inefficiency and enhance workforce quality and well-being in weak institutional environments.

We revisit the employer size wage effect (ESWE) – arguably the most basic and influential departure from the law of one price for labor. Our main result is that this canonical fact disappears completely across establishments within the same firm, even though they operate in different local labor markets. We uncover and dissect this fact by including a firm fixed effect in otherwise standard cross-sectional regressions of wages on establishment size. We implement this demanding specification in population-wide triple-linked firm-establishment-employee data in Germany. This result is new in the ESWE literature (for which our paper also provides the first systematic meta-analysis). This wage-size decoupling is hard to square with the view that employment is determined along a finitely elastic employerspecific labor supply curve – i.e., employers pay exactly the minimum needed for the quantity of labor, but no more – the foundation of the monopsony view. By contrast, large multi-establishment firms (MEF) appear to hire off their labor supply curves (or those curves are very elastic), pay wage premia above the monopsonistic minimum, and leave excess labor supply. We find some evidence for a reemergence of the ESWE within low-premium MEFs. Overall, at least for the 25% of German employment in large firms for which the ESWE disappears, wage setting and employment determination may be better accounted for by alternative models, namely accommodating above-market-clearing wage premia and rationing of labor supply, such as efficiency wage theories.

We investigate the relationship between county-level social capital in the U.S. and asymmetric earnings timeliness (accounting conservatism). We measure social capital by the strength of civic norms and the density of social networks in a community. We find that firms headquartered in regions with higher social capital have earnings that reflect bad news more quickly than good news. Two potential mechanisms driving this connection are evident in our findings. First, the positive link between social capital and asymmetric earnings timeliness is more pronounced in firms with weaker external oversight, suggesting that social capital compensates for weaknesses in these mechanisms by discouraging managers from delaying the recognition of bad news. Second, we illustrate that firms in high social capital regions are more likely to recruit senior executives with higher asymmetric earnings timeliness coefficients. This result implies a preference for managers who adopt more conservative accounting practices. We find similar results using an international sample of firms from 21 countries. Our findings offer new insights into how local social norms influence corporate financial reporting.

We study how idiosyncratic income risk shapes the aggregate and distributional effects of labor and capital income taxation in dynamic general equilibrium models. To this end, we compare a heterogeneous-agent (HA) model with uninsurable idiosyncratic labor productivity risk and a ten-representative-agent (TE) model in which households correspond to fixed wealth deciles without such risk. At the aggregate level, both models generate qualitatively similar responses; however, the HA model exhibits a smaller recessionary impact driven by precautionary savings behavior, which stabilizes investment. At the distributional level, the models differ sharply. In the HA framework, tax shocks trigger endogenous mobility across wealth deciles. These inter-decile transition dynamics tend to benefit lower deciles. In contrast, the TA model features fixed household positions. Our findings highlight that while simpler multi-representative-agent models can approximate aggregate dynamics well, they may miss important distributional adjustment channels. The relevance of these mechanisms ultimately depends on the empirical importance of mobility across the wealth distribution, pointing to a key trade-off between model simplicity and accuracy.

Forecasts that minimize mean squared forecast error (MSE) often exhibit excessive volatility, limiting their practical applicability. We address this accuracy-smoothness trade-off by introducing a Multivariate Smooth Sign Accuracy (M-SSA) framework, which extracts smoothed components from leading indicators to enhance the signal-to-noise ratio and control the forecast volatility and timing. Applied to quarterly German GDP growth, our method yields smoothed forecasts that can improve forecasting accuracy, particularly over medium-term horizons. We find that while smoother forecasts tend to lag slightly around turning points, this can be offset by adjusting the forecast horizon. These findings highlight the practicality of the M-SSA framework for both forecasters and policymakers, especially in settings where forecast revisions or policy adjustments are costly.

Based on a sufficient statistics approach, we show how the state of technology of European industries relative to the rest of the world can be empirically assessed in a way that is simple in terms of computation, parsimonious in terms of data requirements, but still comprehensive in terms of information. The lack of systematic cross-industry correlation between export specialization and technological advantage suggests that standard measures of revealed comparative advantage only imperfectly capture a country’s technological prowess due to the concurrent influences of factor prices, market size, markups, firm selection and market share reallocation. These findings offer policy insights relevant to the EU’s external competitiveness debate, echoing several recommendations from the Draghi report. Achieving export specialization in key sectors requires more than just technological superiority.

Climate policy design must balance emissions mitigation with concerns for fairness, particularly as climate change disproportionately affects the poorest households within and across countries. Integrated Assessment Models used for global climate policy evaluation have so far typically not considered inequality effects within countries. To fill this gap, we develop a global Integrated Assessment Model representing national economies and subnational income, mitigation cost, and climate damage distribution and assess a range of climate policy schemes with varying levels of effort sharing across countries and households. The schemes are consistent with limiting temperature increases to 2 °C and account for the possibility to use carbon tax revenues to address distributional effects within and between countries. We find that carbon taxation with redistribution improves global welfare and reduces inequality, with the most substantial gains achieved under uniform taxation paired with global per capita transfers. A Loss and Damage mechanism offers significant welfare improvements in vulnerable countries while requiring only a modest share of global carbon revenues in the medium term. The poorest households within all countries may benefit from the transfer scheme, in particular when some redistribution is made at the country level. Our findings underscore the potential for climate policy to advance both environmental and social goals, provided revenue recycling mechanisms are effectively implemented. In particular, they demonstrate the feasibility of a welfare improving global climate policy involving limited international redistribution.

We examine how banks manage carbon transition risk by selling loans given to polluting borrowers to less regulated shadow banks in securitization markets. Exploiting the election of Donald Trump as an exogenous shock that reduces carbon transition risk, we find that banks engage in regulatory arbitrage and use brown loan securitization to manage their exposure to carbon transition risk. Banks are more likely to securitize brown loans when carbon transition risk is high but keep these loans on their balance sheets when the risk is reduced. In addition, securitization enables banks to offer lower interest rates to polluting borrowers but does not affect the supply of green loans. Our findings are more pronounced among banks with low levels of capitalization, domestic banks, and banks that do not display green lending preferences. We discuss how securitization can weaken the effectiveness of bank climate policies.

Why are children with lower socioeconomic status (SES) substantially less likely to be enrolled in child care? We study whether barriers in the application process work against lower-SES children — the group known to benefit strongest from child care enrollment. In an RCT in Germany with highly subsidized child care (N = 607), we offer treated families information and personal assistance for applications. We find substantial, equity-enhancing effects of the treatment, closing half of the large SES gap in child care enrollment. Increased enrollment for lower-SES families is likely driven by altered application knowledge and behavior. We discuss scalability of our intervention and derive policy implications for the design of universal child care programs.