Relying upon an original (country-sector-year) measure of robotic capital ($RK$), we investigate the degree of complementarity/substitutability between robots and workers at different skill levels. We employ nonparametric methods to estimate elasticity of substitution patterns between $RK$ and skilled/unskilled labor over the period 1995–2009. We show that: i) on average, $RK$ exhibits less substitutability with skilled workers compared to unskilled workers, indicating a phenomenon of “RK-Skill complementarity”. This pattern holds in a global context characterized by significant heterogeneity; ii) the dynamic of “RK-Skill complementarity” has increased since the early 2000s; iii) the observed strengthening is more prominent in OECD countries, as opposed to non-OECD countries, and in the Manufacturing sector, compared to non-Manufacturing industries.

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.

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.

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.

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 examines the effects of heterogeneous biased expectations between the young and old on business cycles and explores its policy implications. Empirical findings reveal that individuals, particularly the young, can have more optimistic or pessimistic views about the future state of the economy compared to the data-generating measure. This study relates these results to the learning-from-experience literature, which suggests that individuals, particularly the young, place greater weight on recent observations when forming their expectations. Incorporating household weighting schemes into a life-cycle learning model, I show that household sensitivity to recent observations amplifies the effects of economic shocks. However, the amplification effects become less extensive as the population ages due to the lower sensitivity of the old. My simulation results indicate that a 10 percentage point increase in the old population ratio leads to a 16 percent decrease in output volatility. Regarding policy implications, this paper suggests that the government spending multiplier declines by approximately 10 percent when the old population ratio rises by 10 percentage points due to weak amplification effects. Moreover, the weakened output effects deteriorate the welfare of the population, particularly that of the young.

Data show that an increase in the Gini coefficient is associated with a falling bottom $p_{B}$% income share and an increasing top $p_{T}$ % income share where, for example $p_{B}$ = 40 and $p_{T}$ = 1. This relationship, which we call the $X$ inequality relationship, is pervasive in the sense that it is observed in many countries, including the US, the UK, France and others. The purpose of this paper is (i) to construct a Schumpeterian growth model to explain the relationship, and (ii) to identify/quantify factors behind it via calibration of the US economy. Our model gives rise to a double-Pareto distribution of income as a result of entrant and incumbent innovations. Its advantage is that it allows us to develop iso-Gini loci and iso-income share schedules in a tractable way. Using a double-Pareto distribution as an approximation of an underlying income distribution, calibration analysis reveals that a declining business dynamism and fiscal policy changes in the past decades played a significant role in generating the $X$ inequality relationship in the US.

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.

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.

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.

We quantify the importance of endogenous human capital and of selection effects for counterfactual analysis of social security (SS) reforms. The literature typically performs these analyses by using structural models featuring exogenous productivity profiles. However, this approach faces two issues: (i) the estimation of productivity is subject to selection bias, and (ii) productivity is endogenous to the SS reforms. In this paper, we estimate a quantitative overlapping generations model featuring endogenous human capital accumulation using US data. First, we eliminate the SS and find a large positive effect on aggregate effective labor supply (${+}10.31\%$). Next, we build variants of this model to quantify the two issues (i) and (ii). We find that the endogeneity issue (ii) is quantitatively more important than the selection bias issue (i).

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.

This article studies how sudden changes in bank credit supply impact economic activity. I identify shocks to bank credit supply based on firms’ aggregate debt composition. I use a model where firms fund production with bonds and loans. In the model, bank shocks are the only type of shock that imply opposite movements in the two types of debt as firms adjust their debt composition to new credit conditions. Bank shocks account for a third of output fluctuations and are predictive of the bond spread.

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.

What is the relationship between short-run fluctuations in economic activity and the long-run evolution of the economy? There is empirical evidence that more perturbed economies tend to grow less. Yet matching this evidence has proven challenging for growth models without market failures. This paper examines the relationship between short-term fluctuations and long-term growth within a complete-market economy featuring Epstein-Zin preferences and unbounded growth driven by human and physical capital accumulation. With these preferences, risk aversion and intertemporal elasticity of substitution are allowed to be independent of each other. When the model is plausibly calibrated, the relationship between the mean and variance of growth turns out to be negative. In most cases, the effect of fluctuations on welfare is found to be negative and sizable, even when the long-run effect on growth is positive.

This paper assesses the role of political tensions between the USA and China and global market forces in explaining oil price fluctuations. To this end, we take part of the previous literature, which highlights (i) the importance of political events in explaining oil price dynamics, (ii) time-varying patterns in the oil market, and (iii) asymmetries in the impact of political tensions and uncertainty on oil prices. While this literature generally focuses on one of these features, we account for all of them simultaneously, allowing for a complete and meaningful investigation of political tensions on oil prices. To this end, we rely on quantile autoregressive distributed lag error-correction models, which are specifically designed to address both the long-run and short-run dynamics across a range of quantiles in a fully parametric setting. Our results show evidence of a quantile-dependent long-term relationship between oil prices and their determinants over the 1958–2022 period, which is also time varying across quantiles: the adjustment speed toward the long-term equilibrium is faster for the highest quantiles, fluctuating between 4% and 6% in the recent period. Overall, our findings highlight the increased role played by China in the oil market since the mid-2000s.

In a monetary model based on Lagos and Wright (2005) where unsecured credit and money are used as means-of-payments, we analyze how the cost and quality of the record-keeping technology affect welfare. Specifically, monitoring agents’ debt repayment is costly but is essential to the use of unsecured credit because of limited commitment. To finance this cost, fees on credit transactions are imposed, and the maximum credit limit that is incentive compatible depends on such fees and monitoring level. Alternatively, the use of money avoids such costs. A higher credit limit does not necessarily improve welfare, especially when the limit is high: the benefit from increased trade surpluses from a higher credit limit is offset by the increased cost of monitoring to achieve the improvement. Moreover, under the optimal arrangement, optimal credit limit decreases with the marginal cost of monitoring. When the cost is sufficiently low, a pure credit equilibrium is optimal. When the marginal cost is high, it is optimal to have a pure-currency economy. But when the cost is at an intermediate level, we show that credit is sustainable but not socially optimal. In this range, the implementable credit limit leads to a higher trade surplus than in a pure monetary economy, but owing to the cost of operating the record-keeping system, social welfare in credit equilibrium is lower than the welfare in a pure monetary equilibrium. In addition, we show that there can be a non-monotonic relationship between the optimal record-keeping level and the optimal credit limit.

In this paper I examine the effect of introducing an account-based central bank digital currency (CBDC) on liquidity insurance and monetary policy implementation. An asset-exchange model is constructed with idiosyncratic liquidity risk, in which one type of agents require currency and/or CBDC to consume while the other type of agents can use any assets to trade. There arises a liquidity insurance to distribute assets efficiently by type. Since central bank reserve accounts are accessible by the public directly, the large excess reserves (LER) in a floor system can make it difficult to separate the types under private information. Therefore, raising the interest on reserves in the floor system can reduce the aggregate liquidity excessively, and the equilibrium allocation with the LER can be suboptimal.

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.