This paper examines the dependence structure and risk spillovers between oil prices and exchange rates in both oil-exporting and oil-importing countries. Using a flexible dependence switching copula model, we analyze both positive and negative dependence and transitions between the dependence regimes. Additionally, we investigate the directional risk spillovers between oil and currency markets in both their downsides and upsides. Based on empirical data from 1999 to 2024 for major oil-exporting and oil-importing countries, we find that oil price-currency dependence is predominantly positive for oil-exporting countries, with infrequent transitions, but mainly negative for oil-importing countries, with frequent transitions between the two dependence regimes. These transitions often occur around crisis or war times. Furthermore, we observe that during downturns in the oil market, tail dependence between oil prices and currencies becomes more pronounced than during upturns. Our results indicate the presence of risk spillovers between oil and currency markets, with the downside spillover effects outweighing the upside ones. Moreover, we find that risk spillover is stronger from oil markets to currency markets than the reverse direction. These insights substantially enrich the existing literature and would offer valuable implications for effective risk management strategies and policymaking.

Rising income and wealth inequality across the developed world has prompted a renewed focus on the mechanisms driving inequality. This paper contributes to the existing literature by studying the impact from life-cycle savings, intergenerational transfers, and fertility differences between the rich and the poor on the wealth distribution. We find that bequests increase the level of wealth inequality and that fertility differences between the rich and the poor amplify this relationship. The counterfactual exercises show that the interaction between bequests and differential fertility is quantitatively important for understanding wealth inequality in the United States.

We provide empirical evidence that the impact of quantitative easing (QE) programs on investment is weaker for countries with high-credit market regulations. We then extend a simple DSGE model with segmented financial markets to include credit regulation and examine its impact on the transmission of conventional and unconventional monetary policies. In our model, the government requires banks to hold a fraction of their assets in government debt. We show that the presence of such regulation can invert monetary transmission under QE policy: An expansionary QE program raises term premiums on corporate bonds and causes a contraction instead of an expansion in the economy. Such a perversion is absent under conventional policy. Further, in contrast to Carlstrom et al. (2017), we show that a simple Taylor rule welfare dominates a term premium peg under financial shocks, while the peg does better in the case of non-financial shocks.

This article analyses the endogenous choice of farmers to be organic or conventional in a groundwater evolutionary model when a tax on fertiliser on conventional farmers is implemented by a regulatory agency. The analysis of the model shows that the coexistence of both type of farmers only occurs when the decrease in productivity due to organic production is relatively low and the price premium for organic products is relatively high. However, even if conversion is welfare improving, our results show that this conversion may be done at the expense of the water resource with a lower water table. An application to the Western la Mancha aquifer (Spain) illustrates the main results.

This paper empirically examines the dynamic relationship between stock market volatility and commodity prices through the time-varying risk aversion channel using daily data between December 31 in 1999 and June 14 in 2021. We employ a time-varying structural-form vector autoregressive model (VAR) model with (aggregate, sectoral and sixteen individual) commodity prices. The results suggest that the transmission mechanism of stock market volatility shocks on the commodity prices change over time. The negative effect of stock market volatility on commodity prices is more statistically significant in the 2008–09 Global Financial Crisis than that during the COVID-19 pandemic in 2020. Further, the effect is greater in energy commodities compared to the agricultural and metals markets. The long-lasting negative effect of risk aversion is stronger compared to that of the expected stock market volatility on the commodity price. The change in the stock-commodity transmission mechanism is likely due to changes in underlying sources of risk aversion and expected uncertainty over time.

U.S. states are sovereign entities and can’t declare bankruptcy as cities and municipalities. This paper examines the impact of a switch in sovereign bankruptcy rules that allows declaring bankruptcy from an economics model perspective. Allowing bankruptcy increases ex-ante risks for the government to refuse repayment, but provides ex-post benefits of reducing default costs and saving federal bailouts. This paper provides a simple framework to analyze this tradeoff. Event analysis shows that an unexpected switch in bankruptcy rules that allows for bankruptcy would decrease government debt-to-GDP ratio by 9.2 percentage points, increase consumption by 0.69 percent, but increase spread by 1.1 percentage points.

We extend the growth-at-risk (GaR) literature by examining US growth risks over 130 years using a time-varying parameter stochastic volatility regression model. This model effectively captures the distribution of GDP growth over long samples, accommodating changing relationships across variables and structural breaks. Our analysis offers several key insights for policymakers. We identify significant temporal variation in both the level and determinants of GaR. The stability of upside risks to GDP growth, as seen in previous research, is largely confined to the Great Moderation period, with a more balanced risk distribution prior to the 1970s. Additionally, the distribution of GDP growth has narrowed significantly since the end of the Bretton Woods system. Financial stress is consistently associated with higher downside risks, without affecting upside risks. Moreover, indicators such as credit growth and house prices influence both downside and upside risks during economic booms. Our findings also contribute to the financial cycle literature by providing a comprehensive view of the drivers and risks associated with economic booms and recessions over time.

This paper distinguishes news about short-lived events from news about changes in longer term prospects using surveys of expectations. Employing a multivariate GARCH-in-Mean model for the US, the paper illustrates how the different types of news influence business cycle dynamics. The influence of transitory output shocks can be relatively large on impact but gradually diminishes over two to three years. Permanent shocks drive the business cycle, generating immediate stock price reactions and gradually building output effects, although they have more immediate output effects during recessions through the uncertainties they create. Markedly different macroeconomic dynamics are found if these explicitly identified types of news or uncertainty feedbacks are omitted from the analysis.

The paper builds a parsimonious US business cycle SVARMA model, establishing identification conditions for independent monetary shocks. The SVARMA model, utilizing Divisia M3 and Divisia M4, is compared to the simple sum M2. The monetary rule with Divisia M3 yields theoretically consistent results marked by the absence of the usual price and liquidity puzzles. As the Federal Reserve (Fed) took a more hawkish approach to curb inflation, significant increases in US interest rates and declines in monetary aggregates were largely influenced by the Fed’s reaction function, which incorporates the Divisia M3 monetary rule. Findings emphasize the monetary impact on the business cycle, highlighting the significance of Divisia monetary aggregates. Historical and variance decompositions reveal diverse, dynamic effects of monetary shocks on macroeconomic variables. The SVARMA model with Divisia M3 and M4 demonstrates superior performance over simple sum M2 in capturing the time path of monetary shocks.

A large literature has shown money demand functions constructed from simple-sum aggregates are unstable. We revisit the controversy surrounding the instability of money demand by examining cointegrating income-money relationships with the Divisia monetary aggregates for the U.S., and compare them with their simple-sum counterparts. We innovate by conducting a more granular analysis of various monetary assets and their associated user costs. We find characterizing money demand with simple-sum measures only works well in a period preceding 1980. Divisia aggregates, their components, and their user costs provide a more reliable interpretation of money demand. Subsample analysis across 1980 and 2008 suggests the instability of money demand is a matter of measurement rather than a consequence of a structural change in agents’ preference for monetary assets.

We propose a stock market model with chartists, fundamentalists and market makers. Chartists chase stock price trends, fundamentalists bet on mean reversion, and market makers adjust stock prices to reflect current excess demand. Fundamentalists’ perception of the stock market’s fundamental value is subject to animal spirits. As long as the stock market is relatively stable, fundamentalists neutrally believe in a normal fundamental value. However, fundamentalists optimistically (pessimistically) believe in a high (low) fundamental value when the stock market rises (falls) sharply. Our framework may produce boom-bust stock market dynamics that coevolve with waves of optimism and pessimism for parameter settings that would ensure globally stable stock market dynamics in the absence of animal spirits. Responsible for such a surprising outcome is the destabilizing nature of temporarily attracting virtual fixed points, brought about by animal spirits.

This paper develops a monetary R&D-driven endogenous growth model featuring endogenous innovation scales and the price-marginal cost markup. To endogenize the step size of quality improvement, we propose a tradeoff mechanism between the risk of innovation failure and the benefit of innovation success in R&D firms. Several findings emerge from the analysis. First, a rise in the nominal interest rate decreases economic growth; however, its relationship with social welfare is ambiguous. Second, either strengthening patent protection or raising the professional knowledge of R&D firms leads to an ambiguous effect on economic growth. Third, the Friedman rule of a zero nominal interest rate fails to be optimal in view of the social welfare maximum. Finally, our numerical analysis indicates that the extent of patent protection and the level of an R&D firm’s professional knowledge play a crucial role in determining the optimal interest rate.

Teenage childbearing is a common incident in developed countries. However, teenage births are much more likely in the USA than in any other industrialized country. Most of these births are delivered by female teenagers from low-income families. The hypothesis put forward here is that the welfare state (a set of redistributive institutions) has a significant influence on teenage childbearing behavior. We develop an economic theory of parental investments and the risky sexual behavior of teenagers. The model is estimated to fit stylized facts about income inequality, intergenerational mobility, and the sexual behavior of teenagers in the USA. The welfare state institutions are introduced via tax and public education expenditure functions derived from US data. In a quantitative experiment, we impose Norwegian taxes and education spending in the economic environment. The Norwegian welfare state institutions go a long way in explaining the differences in teenage birth rates between the USA and Norway.

This study investigates the effect of government size, as measured by the tax revenue to gross domestic product (tax-GDP) ratio, on output responses to increases in government purchases. First, we show that in a standard static neoclassical model, the stimulus effect of fiscal expansion on output increases with the tax-GDP ratio. This finding is quantitatively confirmed using a dynamic neoclassical model with standard functional forms and parameter values. To empirically test the theoretical findings, we analyze the responses of macroeconomic variables to an unanticipated increase in government purchases for 12 Organisation for Economic Cooperation and Development (OECD) countries during 1985–2019 using a state-dependent local projection method. The estimation results reveal that while output responses to an unanticipated fiscal expansion are significantly positive when the tax-GDP ratio is high, they are statistically indistinguishable from zero when the ratio is low. Overall, our findings suggest that fiscal expansion can stimulate output more effectively at high tax rates, unlike the well-known predictions of the traditional Keynesian model.

Motivated by distributional concerns raised by recent breakthroughs in AI and robotics, we ask how workers would prefer to manage an episode of automation in a task-based model, which distinguishes between automation and traditional technical progress. We show that under majority voting with the option to implement a “partial” UBI (as transfers to workers) it is optimal to tax capital at a higher rate than labor in the long run to fund the partial UBI. We show that, unlike traditional technical progress, automation always lowers the labor share in the long run, justifying distributional concerns. A quantitative analysis of an episode of automation for the US economy shows that it is optimal from the workers’ perspective to lower capital taxes and transfers over the transition. Nevertheless, this policy increases worker welfare by only 0.7% in consumption-equivalent terms, compared with a 21.6% welfare gain to entrepreneurs, because the welfare gains to workers from lower capital taxes are second-order, while the gains to entrepreneurs are first-order.

One of the challenges of population aging is the rising demand of elder care. Adult children fill a substantial portion of this care need. To understand its implication on their labor market choices and welfare outcomes, we build a simple static model where households can spend time and money producing care. We calibrate the model using data from the American Community Survey, the Health and Retirement Study, and National Health and Aging Trends Study/National Study of Caregiving to match moments in the labor market and caregiving patterns. With the calibrated model, we consider a few government programs under a projected aging population structure. Our results show that care subsidy and Medicaid expansion both cause a shift from informal care to formal care, relieving adult children from care burdens and thus improving their welfare. Caregiver allowance appears to have little effects on caregiving behaviors, which leads to minimal welfare improvement.

The international migration literature has highlighted four key stylized facts from the perspective of the source country: (i) Migration rates are notably high, with some nations seeing over ten percent of their population living abroad. (ii) Certain developing countries have witnessed a significant exodus of skilled workers, commonly referred to as brain drain, spanning several decades. (iii) Migrants often maintain strong ties to their country of origin, evidenced by the substantial remittances they send back to their relatives. (iv) Migration is not necessarily permanent, as a considerable number of individuals return to their home country after a period spent abroad. In this paper, we present a theoretical model that endogenously explains these facts. Our model allows us to explore key issues in migration literature from a theoretical standpoint. We analyze the general equilibrium effects of migration, its long-term implications, and its welfare consequences. Additionally, we investigate whether the combined impact of return migration and remittances can counterbalance the effects of skilled migration. Finally, we evaluate the efficacy of policy interventions designed to mitigate the adverse effects of brain drain.

We use the New Keynesian Dynamic Stochastic General Equilibrium (DSGE) framework and Vector Autoregressive (VAR) to investigate the usefulness and relevancy of monetary services, augmented to include credit card transaction services. We use the new credit-card-augmented Divisia monetary aggregates in the models to further the existing research on their usefulness and relevancy. In this research, we compare three different monetary aggregates within the New Keynesian framework: (1) the aggregation-theoretic “true” monetary aggregate, (2) the credit-card-augmented Divisia monetary aggregate, and (3) the simple sum monetary aggregate.

We acquire the following primary results. (1) The credit-card-augmented Divisia monetary aggregate tracks the theoretical (true) monetary aggregate, while simple sum does not. Although this result would be expected from the theory in classical economic models, the result is not an immediate implication of the theory in New Keynesian models and therefore needs empirical confirmation. (2) Under the recursive VAR framework, the credit-card-augmented Divisia monetary aggregate serves as a preferable monetary policy indicator compared to the traditional federal funds rate. (3) On theoretical grounds, we find that the separability condition for existence of a monetary aggregator function could fail, if credit card deferred payment services were excluded from the monetary services block, unless all markets are perfect.

This paper identifies several ways in which “measurement matters” in detecting quantity-theoretic linkages between money growth and inflation in recent data from the Euro Area, United Kingdom, and USA. Elaborating on the “Barnett critique,” it uses Divisia aggregates in place of their simple-sum counterparts to gauge the effects that monetary expansion or contraction is having on inflationary pressures. It also uses one-sided time series filtering techniques to track, in real time, slowly shifting trends in velocity and real economic growth that would otherwise weaken the statistical money growth-inflation relationship. Finally, it documents how measures of inflation based on GDP were distorted severely, especially in the EA and UK, during the 2020 economic closures. Using measures based on consumption instead, estimates from the P-star model confirm that changes in money growth have strong predictive power for subsequent movements in inflation.

Is the working capital channel big, and does it vary across industries? To answer this question, I estimate a dynamic stochastic macro-finance model using firm-level data. In aggregate, I find a partial channel —about three-fourths of firms’ labor bill are borrowed. However, the strength of this channel varies across industries, reaching as low as one-half for retail firms and as high as one for agriculture and construction. This provides evidence that monetary policy could have varying effects across industries through the working capital channel.