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.

The paper looks at the question of measuring the importance of shocks to cycles. We consider two types of cycles - oscillations and those summarized by the NBER that require a study of growth in activity to establish turning points in the level of activity. The latter demarcate expansions and contractions. We establish a connection between these two concepts of cycles that shows shocks may have very different effects on each. As an application we look at a question that has often been asked over how important technology shocks are to cycles in activity? Some recent research concludes that total factor productivity (TFP) shocks are not important for oscillations and therefore models should be designed to reflect that. Using the same data we show that TFP shocks are very important to both types of cycles.

Post the great financial crisis (GFC) of 2008–2009, there has been a surge in the macroeconomics literature on aggregate uncertainty. Although the recent literature has recognized the adverse real effects of global uncertainty shocks in emerging market economies (EMEs), the role of monetary policy in offsetting these adverse effects and their link with the exchange rates is not explored in the literature. We find that the currently followed interest rate rules (IRRs) under a flexible inflation-targeting regime are ineffective in stabilizing the domestic economy during periods of high global uncertainty in the EMEs. Using a small open economy new Keynesian DSGE model with Epstein–Zin preferences and second-moment demand shocks, we compare and propose alternate monetary policy rules that significantly reduce welfare losses. We find that the best monetary policy rule in terms of welfare depends on the nature of shock that is, first-moment or second-moment shock.

The role of capital in measuring resilience is investigated. Focusing on the current short-run and potential long-run growth paths of the economic system, we propose new indexes to separately measure adaptability and resistance to shocks, which are the essence of a system’s resilience. Capital dynamics during the transition and along the balanced growth path are used here instead of employment to represent the evolution of the size and composition of the economy. Our indexes measure adaptability and resistance by comparing the two capital growth rates. They are built by mimicking the average and variance of the difference in growth rates. In this new setting, investment and depreciation flows play an important role in explaining what the partial index of adaptability reveals. The available data on the USA and Spanish capital allow us to empirically compute the indexes and draw conclusions about their ability to resist shocks and absorb their effects. We conclude that the US economy is more adaptable and has a greater capacity to absorb impacts than the Spanish economy, but it is less resistant to disturbances.

Over a thousand years, military employment rises, peaks, and then falls. I argue that rising military shares were driven by structural change out of agriculture, and the recent declines are driven by substitution from soldiers toward military goods. I document evidence for this substitution effect and introduce a model of growth and warfare that reproduces the time series patterns of military expenditure and employment. The model also correctly predicts the cross-sectional patterns, and that military employment and expenditure shares are decreasing in income during wars. Finally, I show that faster economic growth can reduce military expenditure in the long run.

Following the introduction of the one-child policy in China, the capital-labor ratio of China increased relative to that of India, while FDI/GDP inflows to China versus India simultaneously declined. These observations are explained in the context of a simple neoclassical overlapping generations paradigm. The adjustment mechanism works as follows: the reduction in the growth rate of the (urban) labor force due to the one-child policy increases the capital per worker inherited from the previous generation. The resulting increase in China’s domestic capital-labor ratio thus "crowds out" the need for foreign direct investment (FDI) in China relative to India. Our paper is a contribution to the nascent literature exploring demographic transitions and their effects on FDI flows.

An article published in 2018 by J.D. Hamilton gained significant attention due to its provocative title, “Why you should never use the Hodrick-Prescott filter.” Additionally, an alternative method for detrending, the Hamilton regression filter (HRF), was introduced. His work was frequently interpreted as a proposal to substitute the Hodrick–Prescott (HP) filter with HRF, therefore utilizing and understanding it similarly as HP detrending. This research disputes this perspective, particularly in relation to quarterly business cycle data on aggregate output. Focusing on economic fluctuations in the United States, this study generates a large amount of artificial data that follow a known pattern and include both a trend and cyclical component. The objective is to assess the effectiveness of a certain detrending approach in accurately identifying the real decomposition of the data. In addition to the standard HP smoothing parameter of $\lambda = 1600$, the study also examines values of $\lambda ^{\star }$ from earlier research that are seven to twelve times greater. Based on three unique statistical measures of the discrepancy between the estimated and real trends, it is evident that both versions of HP significantly surpass those of HRF. Additionally, HP with $\lambda ^{\star }$ consistently outperforms HP-1600.

This paper develops a multivariate filter based on an unobserved component model to estimate the financial cycle. Our model features: (1) a dynamic relationship between the financial cycle and key variables; (2) time-varying shock volatility for trend and cycle components. We demonstrate that our approach not only exhibits superior early warning properties for banking crises but also outperforms commonly used indicators in terms of data fit for decomposition exercises, as evidenced by the higher marginal likelihood. We document three important properties of the financial cycle. First, the sensitivity of the financial cycle to changes in real estate valuations increased during the post-90s period. Second, the sensitivity of the cycle to changes in financial conditions displays volatility and country specificities. Finally, our reduced form estimates suggest that the banking crisis of 1988 was preceded by positive contributions from the risk appetite shock, while the primary source of vulnerabilities emanated from the housing market in the run-up to the Global Financial Crisis.

Experimental evidence shows that human subjects frequently rely on adaptive heuristics to form expectations but their forecasting performance in the lab is not as inadequate as assumed in macroeconomic theory. In this paper, we use an agent-based model (ABM) to show that the average forecasting error is indeed close to zero even in a complex environment if we assume that agents augment the canonical adaptive algorithm with a Belief Correction term which takes into account the previous trend of the variable of interest. We investigate the reasons for this result using a streamlined nonlinear macro-dynamic model that captures the essence of the ABM.

Motivated by the sharp increases in public spending following the global financial crisis, we employ the GMM Panel VAR approach at annual frequency between 2004 and 2014 to investigate the dynamic response of alternative income distribution variables to shocks imposed on tax revenues and three key components of social expenditures: social protection, health, and education. We confirm the potential of fiscal policy to reduce income inequality in the medium to longer run, but point to the differential approaches to pursue such a goal in middle- versus high-income countries. We find that the particular expenditure component under consideration matters in terms of the dynamic effect on inequality and on different parts of the income distribution, as well as in terms of the implied time profile. In middle-income countries, positive education spending shocks are the most effective in achieving better distributional outcomes over a medium run of several years. By contrast, in high-income countries, positive health spending and tax shocks have a more pronounced favorable dynamic distributional effect.

We investigate the role and impact of household debt on the economic performance of European economies during the double-dip recession of 2008–2013. We use a loan-level data set of millions of residential mortgages originated between 2000 and 2013 to calculate regional indicators of household debt. The granular information allows us to construct a measure of interest rate mispricing during the housing boom that we use to identify the effect of a credit shock (CS) on household debt. Our analysis provides three main conclusions. First, in the period 2004–2006, the measure of CS was negative in most European regions which indicates that credit conditions were significantly relaxed relative to earlier years. Second, we find that regions in which household leverage increased more rapidly during the 2002–2007 period experienced a more severe decline in output and employment after 2008. Third, we find that the CS had the largest effect on increasing leverage for the low-income and the middle-income households, although the leverage of the high-income households represents a more powerful predictor of the decline in economic activity.

This paper studies the impact of technological progress on unemployment in a search-matching model with heterogeneous multiworker firms. In the model, some firms continue to reap rewards from new technologies over time and contribute to job creation, while other firms obsolesce and reduce their employment. Thus, the model captures an endogenous change in the aggregate composition of firms (the firm-composition effect). Considering this effect along with the two canonical effects—the capitalization and creative-destruction effects—I examine the importance of each through a simulation. The results show that the firm-composition effect explains almost all the variation in unemployment in the model, mainly through shrinking the number of obsolescing firms relative to surviving firms and increasing the aggregate technology adoption rate when technology progresses rapidly.

We are motivated by central bank responses to the rise in inflation in the aftermath of the coronavirus pandemic and investigate monetary policy behavior in advanced and emerging economies. We speak to the debate on whether the conduct of monetary policy in emerging economies is fundamentally different from that in advanced economies. We also address the issue of whether the common practice of using market rates (instead of policy rates) to proxy for the stance of monetary policy leads to different conclusions regarding the cyclicality of monetary policy in emerging economies. Using time series data for the G7 and EM7 countries, we show that the conventional wisdom that monetary policy in emerging economies is different from monetary policy in advanced economies still holds.

We show that trade credit contracts between sectors can provide a useful alternative to fiscal transfers during a major productivity shock. Defaults in credit contracts function as transfers between sectors, which can be implemented through a bankruptcy law or through credit renegotiation. Transfers implemented through defaults allow for a reduction in the size of the fiscal policy that restores the economy to the optimal allocation, constituting a relevant alternative to economies without an available fiscal space to implement the optimal policy.

By introducing automation development into a labor search model, this paper obtains that the increasing importance of automation in production may be responsible for the reduction in job reallocation along the transitional dynamics path. In the long run, we find automation also increases the total unemployment rate and reduces overall labor force participation. In addition, decreasing any disparity between differently skilled labor is detrimental to job reallocation along the transitional dynamics path, and both the long-run total unemployment rate and overall labor market participation will fall. Nevertheless, appropriate government subsidy policies can improve business dynamics across the labor market.

We follow Belongia and Ireland (2021) and investigate the role that the Center for Financial Stability credit card-augmented Divisia monetary aggregates could play in monetary policy and business cycle analysis. We use Bayesian methods to estimate a structural VAR under priors that reflect Keynesian channels of monetary transmission, but produce posterior distributions for the structural parameters consistent with classical channels. We also find that valuable information is contained in the credit-augmented Divisia monetary aggregates and that they perform even better than the conventional Divisia aggregates, in terms of highlighting the role of the money supply in aggregate demand.

Does household debt affect the size of the fiscal multiplier? We investigate the effects of household debt on government spending multipliers using a smooth transition vector autoregression model. Through generalized impulse response functions, we measure whether the effect of government spending on GDP is conditioned by different levels of household debt in Australia, Sweden, and Norway, three countries with high levels of household indebtedness, and in the world’s seven largest economies. Our results indicate that the short-term effects of government spending tend to be higher if fiscal expansion takes place during periods of low household debt. On average, the fiscal multiplier (on impact) is 0.70, 0.61, and 0.79 (percent of GDP) larger when the increase in government spending takes place during periods of low household debt for Australia, Norway, and the United States.

This paper examines how unionization affects economic growth through its impact on industry concentration in a two-country model of international trade and endogenous productivity growth. Knowledge spillovers link firm-level productivity in innovation with geographic patterns of industry ensuring a faster rate of output growth when industry is relatively concentrated in the country with the greater labor supply. We show that stronger bargaining power in the relatively large country increases the rate of output growth when labor unions are employment-oriented but decreases the rate of growth when unions are wage-oriented. We then calibrate the model using labor market data for the United Kingdom and France and study the effects of union bargaining power on industry location patterns, output growth, and national welfare.

This paper studies expectation formation of professional forecasters in the context of the Phillips curve. We assess whether professionals form their expectations regarding inflation and unemployment consistent with the Phillips curve based on individual forecast data taken from the ECB Survey of Professional Forecasters. We consider expectations over different horizons and do not restrict the analysis to point forecasts but we also take the information inherent in density forecasts into account. We explicitly consider the role of anchoring of inflation expectations as potential source of nonlinearity, and we also assess whether the Phillips curve relation translates to a link between uncertainty regarding inflation and unemployment. Our findings show that professionals tend to build their expectations in line with the Phillips curve but this is only observed for expectations made for shorter horizons. For longer horizons, the Phillips curve connection is much weaker. This relationship also depends on the degree of anchoring and results in a connection between uncertainty regarding future inflation and unemployment.