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In this paper, we study the transmission and effectiveness of the public expenditure shock across business cycle phases in the Indian economy. The empirical results suggest that the deflationary impact of the public expenditure shock and the subsequent accommodative response of interest rates exhibit a countercyclical public expenditure multiplier during the contraction period. Moreover, the large and significant negative impact of the public expenditure shock on inflation and the interest rate has resulted in a larger public expenditure multiplier during a supply-side recession than a demand-side recession. Based on empirical evidence, we suggest that policymakers consider the presence of nonlinearities in the transmission and effectiveness of the public expenditure shock while taking fiscal policy measures. [ABSTRACT FROM AUTHOR]

This paper focuses on the spillover dynamics of shocks originating in China during the last two decades. More specifically, the paper compares the effects of a shock to China's GDP and exchange rate using early 2000s trade patterns with those of two decades later. We use a global vector autoregressive (GVAR) model as it allows to consider trade interactions as well as financial linkages through interest rates, stock prices, and exchange rates. Our results indicate that the shock spillovers from China have become more pronounced over the past two decades. While the world has become more exposed to China's economy, it has become more susceptible to Chinese economic shocks. This paper contributes to the literature by evaluating the dynamics of China's spillover effects and highlights the structural changes in trade between major global trade players. [ABSTRACT FROM AUTHOR]

This paper studies the role of banks in the transmission of commodity price shocks in emerging economies when they have access at external debt nominated in a foreign currency to finance their credit operations. Using a SVAR model for six Latin American countries, we find that a positive commodity price shock generates a credit and output expansion up to 46% higher in the presence of banks' balance sheets effects compared with a model when this mechanism is not considered. We also show that the inclusion of financial system variables in the model improves its capacity to replicate the trajectory and volatility of the business cycle. These findings reinforce the necessity to explicitly include the role of the financial system in the explanation of credit and business cycles of emerging economies in the presence of price shocks, contrary to current literature practice. Moreover, it underlines the importance of recent literature studying the effects of financial globalization and potential economic policies (exchange rate policy, macroprudential policy and/or capital controls) to soften the macroeconomic impact of these types of shocks. [ABSTRACT FROM AUTHOR]

This paper proposes a multi-level dynamic factor model to identify common components in output gap estimates. We pool multiple estimates for 157 countries and decompose them into one global, eight regional, and 157 country-specific cycles. Our approach easily deals with mixed frequencies, ragged edges, and discontinuities in the underlying output gap estimates. To restrict the parameter space in the Bayesian state space model, we apply a stochastic search variable selection approach and base the prior inclusion probabilities on spatial information. Our results suggest that the global and the regional cycles explain a substantial proportion of the output gaps. On average, 18% of a country's output gap is attributable to the global cycle, 24% to the regional cycle, and 58% to the local cycle. [ABSTRACT FROM AUTHOR]

This paper presents an approach for estimating changes in firms' productivity. We apply the quantile approach, which estimates the changes in the productivity distribution of surviving firms. Using this method, the paper clarifies productivity dynamics in terms of both average change and dispersion in Japan from 1987 to 2014. The main results of the analysis are as follows: During a boom or normal period, the productivity distribution shifts to the right and the productivity dispersion decreases. Conversely, during a recession, the productivity distribution shifts to the left and the productivity dispersion expands. The analysis also gives quantitatively significant results. During the historically rare global financial crisis of 2008, the weighted (simple) average of manufacturing productivity in Japan fell by only 0.2% (5.4%). We identified that this counter-intuitive result was due to a significant change in the shape of the productivity distribution and found that the crisis would reduce productivity by more than 22% if the effects of changing the shape of the distribution were adjusted. [ABSTRACT FROM AUTHOR]

Based on German business cycle forecast reports covering 10 German institutions for the period 1993–2017, the paper analyses the information content of German forecasters' narratives for German business cycle forecasts. The paper applies textual analysis to convert qualitative text data into quantitative sentiment indices. First, a sentiment analysis utilizes dictionary methods and text regression methods, using recursive estimation. Next, the paper analyses the different characteristics of sentiments. In a third step, sentiment indices are used to test the efficiency of numerical forecasts. Using 12-month-ahead fixed horizon forecasts, fixed-effects panel regression results suggest some informational content of sentiment indices for growth and inflation forecasts. Finally, a forecasting exercise analyses the predictive power of sentiment indices for GDP growth and inflation. The results suggest weak evidence, at best, for in-sample and out-of-sample predictive power of the sentiment indices. [ABSTRACT FROM AUTHOR]

This paper examines the relative significance of oil supply, oil demand, and monetary policy shocks in explaining US macroeconomic variations. We analyze impulse response functions and variance decomposition to assess the relative importance of these shocks. Using a Bayesian structural VAR framework and the penalty function approach, we identify the shocks of interest. We find that oil supply shocks explain less than 3% of the variation in output, but have a relatively larger impact on inflation, accounting for around 13% of the inflation variation. Oil demand shocks explain 3% of output variation, but contribute significantly to inflation variation (around 16%). In contrast, monetary policy shocks have a greater influence on output, explaining approximately 13% of the observed variation. Monetary policy shocks are also the most influential source of inflation variation, contributing over 24% to the overall variation. Based on historical variance decomposition, we find that the recent inflation surge is attributable to both monetary expansion and oil supply factors. Overall, the study highlights the dominance of monetary policy shocks in explaining US macroeconomic fluctuations, with oil supply and demand shocks playing secondary roles. [ABSTRACT FROM AUTHOR]

This paper studies the characteristics of financial cycles (credit and house prices) and their interactions with business cycles in Taiwan. We employ multivariate structural time series model to estimate trend and cyclical components in real bank credit, real house prices, and real GDP. We find that financial cycles are roughly twice the length of the business cycles, and house price cycles lead both credit and business cycles. Nevertheless, the estimated length of business and financial cycles in Taiwan is much shorter than those in industrialized economies. We then use machine learning to evaluate the importance of a macroeconomic variable that predicts downturns of financial cycles, by conducting both in-sample fitting and out-of-sample forecasting. Those macrovariables selected by machine learning reflects Taiwan's close linkage in trades and financial interdependence with other countries such as China and spillover effects from the Fed's monetary policy. [ABSTRACT FROM AUTHOR]

This paper investigates how supply noise and demand noise contribute to business cycle fluctuations in three major European economies. A structural vector autoregressive model is used to identify supply, demand, supply noise and demand shocks. The identification scheme is built on nowcast errors of output growth and the inflation rate that are derived from the Consensus Economics Survey. The results indicate that positive supply noise and positive demand noise shocks have an expansionary effect on output, but their magnitude differs across countries. The two shocks contribute equally to business fluctuations, and jointly, they account for around one quarter of the total variation in GDP in each of the three countries. [ABSTRACT FROM AUTHOR]

In this paper, the natural rate of interest in Denmark, Norway and Sweden is estimated. This is done by augmenting the Laubach and Williams (Rev Econ Stat 85:1063–1070, 2003) framework with a dynamic factor model linked to economic indicators––a modelling choice which allows us to better identify business cycle fluctuations. We estimate the model using Bayesian methods on data ranging from 1990Q1 to 2022Q4. The results indicate that the natural rate has declined substantially and in all countries is at a low level at the end of the sample. [ABSTRACT FROM AUTHOR]

This paper analyses how short-term fluctuations in economic growth affect inequality in developing countries. Using a sample of 71 countries, we find that, on average, growth upswings are associated with reductions in inequality. This reduction is, however, largely undone by growth slowdowns. A mediation analysis framework helps identify unemployment, especially youth unemployment, as the main channel through which fluctuations in growth affect the dynamics of inequality. These findings suggest that both the quality of jobs created, and labor market policies are important to ensure that growth outcomes are conducive to inequality reduction. [ABSTRACT FROM AUTHOR]

This paper examines whether productivity news shocks were among the drivers of the Great Recession. To do this, the Smets and Wouters (Am Econ Rev 97(3):586–606, 2007. https://doi.org/10.1257/aer.97.3.586) model is extended by a generalized preference specification which allows for scaling wealth effects on the labor supply. The resulting model is estimated using Bayesian methods which draw upon the US data from the period 1965Q2 to 2014Q3. There are four main results: (i) Estimation of the model is inconclusive regarding the degree of wealth elasticity of the labor supply. As a result, two complementary versions of the model prevail, each of which has differing implications for the transmission and the quantitative importance of exogenous shocks. (ii) When the degree of wealth elasticity of the labor supply is low, news shocks replace risk premium shocks, suggesting that news shocks are one possible reason for fluctuations in US business cycles. (iii) When the Great Recession period is analyzed through the lenses of the two complementary versions of the model, two explanations emerge as potential reasons behind the deepening of the crisis: worsening credit conditions as well as the collapse of over-optimistic expectations regarding future productivity. (iv) For both model specifications, general developments in productivity are estimated to be positive. Therefore, productivity slowdown is not considered to be among the reasons for the emergence or persistence of the Great Recession. [ABSTRACT FROM AUTHOR]

This study examines the state-dependent effects of crude oil price shocks on the US aggregate economy. Using a smooth transition vector autoregressive model, we assess the effects of normalized supply and demand shocks in the global oil market over the different phases of the business cycle. Our findings show that the link between oil prices and macroeconomic dynamics is nonlinear and that structural shocks in the oil market conditional on recessions have a greater and more persistent contractionary impact on macroeconomic variables including industrial production, employment, and consumer price inflation. Forecast error variance decomposition confirms that oil prices have much stronger stagflationary effects during recessions. [ABSTRACT FROM AUTHOR]

We investigate the impact of the financial cycle on fiscal policy by estimating fiscal multipliers for different types of government spending that are contingent on two states determined by the financial cycle. To obtain our estimates, we extend the threshold VAR method from a single country to a panel of high-income countries. Our results indicate that the multiplier for government investment is affected by the state of the financial cycle: while the initial impact is positive for both states, in an upturn it turns negative, while in a downturn it remains positive. In the case of government consumption, the multiplier does not seem to significantly depend on the financial cycle. However, jointly conditioning on the financial and business cycles produces multipliers of government consumption which vary over the states of both cycles. This contrasts with the results for government investment which are left essentially unchanged by the joint conditioning on the four states defined by both cycles. [ABSTRACT FROM AUTHOR]

This document estimates an unobserved components model to examine the connection between the business cycle and the natural unemployment rate in Brazil, Colombia, and Mexico. I inquire about the possibility that the unemployment rate in these countries exhibits hysteresis and its nature. The results suggest an absence of hysteresis in Colombia's unemployment rate, supply-driven hysteresis effects in Brazil, and demand-driven hysteresis effects in Mexico. Hysteresis is defined as a dynamic structure in which the cyclical component of the unemployment rate has permanent effects on the natural component. The empirical specification is cast into a Bayesian state-space form and estimated using Markov chain Monte Carlo (MCMC) methods. The specification allows for time-varying hysteresis and stochastic volatility. I use a Bayesian model selection approach to deal with the non-regular test for the null hypothesis of no time variation in the hysteresis parameter and the variances of the innovations. Finally, the document discusses policy implications of findings regarding the degree of development in these countries. [ABSTRACT FROM AUTHOR]

Assessing the momentum of the business cycle is of utmost importance for policymakers and private agents. In this respect, the use of business cycle clocks has gained prominence among national and international institutions to depict the current stage of the business cycle. Drawing on circular statistics, we propose a novel approach to business cycle clocks in a data-rich environment. The method is applied to the main euro area countries resorting to a large data set covering the last three decades. We document the usefulness of the circular business cycle clock to capture the business cycle stage, including peaks and troughs, with the findings being supported by the cross-country evidence. [ABSTRACT FROM AUTHOR]

Business cycle analysis faces the challenge of high-dimensional databases with a time-irregular span. This study addresses these issues to estimate the Brazilian agricultural business cycle by proposing the use of an entropic test of relative information and the estimation of a generalized dynamic factor model in the context of a time-irregular span. In addition, we assess the co-movements between the estimated cycle and a wide range of weather, macroeconomic, and sectoral variables. The main results are: (i) the sharpest crises of the agricultural cycle are associated more with weather events than with Brazil's economic crises, reinforcing that agriculture has a stabilizing role in the aggregated cycles; (ii) among all the variables analyzed, those related to weather (minimum and maximum temperature and precipitation) present the greatest commonalities with the agricultural cycle and are leading indicators; (iii) minimum temperatures and precipitation in states are essentially pro-cyclical, while maximum temperatures are pro-cyclical in typically colder states and counter-cyclical in warmer states; (iv) following the weather variables, credit variables had the highest average commonalities, with phases of expansion in the agricultural cycle leading to contractions in the indicators of arrears and defaults and in the interest rate of rural credit, with some time lag; (v) the behavior of the Brazilian economy and global demand for imports are also antecedent and pro-cyclical, but with relatively smaller commonalities; and (vi) expansions of the agricultural cycle lead to contractions in the unemployment rate of the economy. The contribution of this study is twofold: (1) its methodological innovation and (2) its application to the Brazilian agricultural business cycle, both of which are unprecedented. [ABSTRACT FROM AUTHOR]

Two recession-derivative indicators (RDIs) have been used extensively as forecast objects in business cycle prediction, viz. (1) the target variable takes value 1 if there is a recession starting exactly at a specific horizon in the future, and (2) the target variable takes value 1 if there is a recession starting any time over a specified period in the future. Using daily yield spread as an illustrative predictor, we formally and quantitatively compare the two RDIs using the receiver operating characteristics analysis. Over 1962–2021 covering eight NBER recessions, we find that generally the second RDI, ceteris paribus, will make the the predictor better performing. However, the first RDI can generate better-looking and more useful predictions under certain scenarios, depending on forecast horizon, recession duration and time profile of signals. We also consider a semiannual chronology proposed by Peláez (J Macroecon 45:384–393, 2015) and find that its performance is in the middle of the other two. Our analysis suggests that the choice of a particular RDI should be dictated by the needs of forecast user in a particular decision making context. [ABSTRACT FROM AUTHOR]

This research contributes to the literature on the effects of fiscal and monetary policy by exploiting non-Gaussianity of the time series for the identification of a Bayesian structural vector autoregression model. Using quarterly US data from 1954:IV to 2006:IV and from 1985:I to 2020:III, we formally assess the plausibility of theoretically predicted signs to label fiscal policy, monetary policy, and business cycle shocks. The impulse responses of consumption to the fiscal policy shock depend to some extent on the sample period, but the implied fiscal multiplier is always less than unity. On investment, there is a lagging crowding-out effect with a high probability, but it is not strongly evident in the latter sample. As for the responses after a contractionary monetary policy shock, we find a weakening output after some lags consistent with the leading monetary policy literature. The business cycle shock turns out to matter for government spending only in the long run, while it is already important for the federal funds rate in the short run. [ABSTRACT FROM AUTHOR]

We develop a new econometric model for the purpose of predicting binary outcomes based on an ensemble of predictors. The method uses the pair-copula construction (PCC) to optimally combine diverse information. As a building block of PCC, the conditional copula is permitted to depend on the conditioning variable in a nonparametric way. This is the major methodological departure from our previous work. We apply this methodology to predict US business cycle peaks 6 months ahead based on the three prominent leading indicators currently used by The Conference Board. In terms of the predictive accuracy as measured by the receiver operating characteristic curve, the proposed scheme is found to do well in comparison with some popular combination models. We have also evaluated the probability forecasts generated from these models using a battery of diagnostic tools, each of which reveals different aspects of skill of the generated forecasts. [ABSTRACT FROM AUTHOR]

So far, empirical research on an ex-post benchmark of the euro adoption has relied on the synthetic control method by Abadie & Gardeazabal (Am Econ Rev 93:112-132, 2003) and Abadie et al. (J Am Stat Assoc 105:493-505, 2010, Am J Polit Sci, 59:495-510, 2015). However, the evidence obtained with this method is not overly consistent, leading to the conclusion that the method is not too robust to different settings of the adjustment screws. Using a new method developed by Harvey & Thiele (J Appl Econ 36:71–85, 2021) based on structural time series models, I find that France and Italy are clear losers from the euro while there are no real winners until 2019. Spain, Netherlands, Greece gain in the period before the financial crisis, but afterwards they lose. In fact, only the German economy is robust to the two crises but it loses until 2008. Relating the theories of optimum currency areas to the estimated gaps of the euro adopters from their synthetic controls, I find that openness, real convergence, and net migration are the main drivers of gains from a euro adoption, while the main drivers of losses are low levels of competitiveness, fiscal instability and labour market rigidity. Examining the crisis channels of the financial and euro crisis shows that fiscal instability, labour market rigidity and also business cycle synchronization cause large losses during the crises. Net migration helps to dampen these shocks. While openness is beneficial during the pre-crises period, it cannot help dampen the shock of the crises. [ABSTRACT FROM AUTHOR]

We construct a Bayesian vector autoregressive model with three layers of information: the key drivers of inflation, cross-country dynamic interactions, and country-specific variables. The model provides good forecasting accuracy with respect to the popular benchmarks used in the literature. We perform a step-by-step analysis to shed light on which layer of information is more crucial for accurately forecasting medium-run euro area inflation. Our empirical analysis reveals the importance of including the key drivers of inflation and taking into account the multi-country dimension of the euro area. The results show that the complete model performs better overall in forecasting inflation excluding energy and unprocessed food over the medium term. We use the model to establish stylized facts on the euro area and cross-country heterogeneity over the business cycle. [ABSTRACT FROM AUTHOR]

We propose measuring business conditions via estimating a smooth function of time that serves as a common factor for explaining the comovement of economic indicators across the occurred business cycles. This smooth measure is useful for reducing the noises in assessing the state of business conditions, and can be easily established using mixed-frequency indicators and updated in real time. We also conduct an empirical study to show its usefulness in real data. [ABSTRACT FROM AUTHOR]