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Fiscal policy is one of the most crucial areas of government economic policy, and it has the potential to influence the economic growth of any nation. According to traditional Keynesian and Ricardian theories, fiscal policy should not be pro-cyclical, and counter-cyclical fiscal policy is the most effective alternative. Furthermore, the periodicity of fiscal policy is also heavily influenced by the quality of political institutions and democracies. Thus, this paper examines the relationship between fiscal policy and economic cycle in Vietnam, a developing economy with dramatic change since 2000. The results support the causal relationship between the set of fiscal policy factors, such as public debt, government tax revenues, and government expenditures, by analyzing quarterly data over a twenty-year period beginning in 2000 by using the Vector Error-Correction Model (VECM). Therefore, the adaptation of fiscal policy to the phases of the economic cycle and the effective deployment of fiscal policy tools help the sustainability of public finances and stimulate economic growth. [ABSTRACT FROM AUTHOR]

This paper uses an estimated Heterogeneous Agent New Keynesian (HANK) model to evaluate the quantitative importance of two channels in driving aggregate consumption fluctuations in the US: (i) precautionary savings against unemployment risk and (ii) MPC heterogeneity. I find that MPC heterogeneity is the dominant channel because a large fraction of households are close to the borrowing limit. The empirical average MPC target in HANK generates counterfactually volatile aggregate consumption, and thus makes it more difficult for the estimated model to match the persistence of the aggregate data, indicating an MPC puzzle. This is because the likelihood‐based estimation favors a low degree of nominal rigidity and responsive monetary policy in the HANK model to reduce the discrepancy between consumption volatility in the model and in the data. The low degree of nominal rigidity and responsive monetary policy reduce the persistence of endogenous variables in the model. [ABSTRACT FROM AUTHOR]

This paper studies how interaction between economic decision-making and environmental awareness affects US business cycle and GHG emissions in a two-sector DSGE model. We emphasize the mechanisms that relate carbon emissions dynamics, consumer behavior, and environmental awareness in a framework incorporating two classes of goods (i.e., "clean" and "dirty"). This paper offers three main results. First, green consumption preferences play a key role in emissions reduction when they internalize emissions concentrations. Second, a green preference shock is the second source of fluctuation in many sectoral variables and stabilizes the business cycle. Third, a pollutant supply shock leads to sustainable consumption procyclicality documented in US data, only if households are environmentally aware. [ABSTRACT FROM AUTHOR]

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This paper aims to evaluate the performances of the wavelet, Hodrick–Prescott (HP), and Baxter–King (BK) filters in extracting cyclical information and to use an appropriate method to analyze China's business cycles. First, we use a second‐order autoregression (AR (2)) and random walk, based on Monte Carlo simulation experiments, to generate the data‐generating processes (DGPs) with different frequency characteristics. Second, the HP, BK, and wavelet filters are applied to extract the cyclical components of the respective DGPs. Third, the filtering abilities of the three methods are statistically compared. The results show the following: (1) Under the condition that the DGP is low frequency (long cycle) and trend dominated, the filtering performance of the three methods will remain unsatisfactory. (2) If the DGP is high frequency (short cycle), all three methods can serve as effective methods regardless of whether they are trend dominated or cycle dominated. However, it can be seen that the BK and wavelet filters present better performance than the HP filter. (3) In other cases, better filtering performances can be observed in the wavelet. Finally, the three methods are applied to estimate China's business cycles. In conclusion, this paper argues that the wavelet can effectively replace HP and BK filters to extract cyclical components. [ABSTRACT FROM AUTHOR]

This paper develops a business cycle model of a small open economy with heterogeneous agents and international labor mobility, with a particular focus on taxes and transfer policies. Migration occurs as a result of the maximization problem of families and, combined with remittances, makes consumption smoothing possible. This paper shows how transfers from the government to young people and elders, funded with distortionary taxes, prompt the migration of people of working age and, among them, some of the most skilled members of the economy. The model is calibrated to match labor mobility in various age–skill groups and aggregate cycle dynamics of the Uruguayan economy, including government transfers and migration volatility. [ABSTRACT FROM AUTHOR]

A key characteristic of heterodox theories of the business cycle is their focus on endogenous business cycle mechanisms. This paper provides an overview and comparison of four models in heterodox business cycle theory: multiplier-accelerator models, Goodwin models, Minskyan debt-cycle models, and momentum trader models. A representative model from each theory is formulated as a two-dimensional predator-prey system in continuous time, which allows us to identify the different stabilizing and destabilizing mechanisms. We argue that the theories are substantially competing, as they posit different mechanisms that explain cycles, but we also argue that these mechanisms are not mutually exclusive. We suggest that heterodox economists work toward a synthesis. [ABSTRACT FROM AUTHOR]

Using data of the EU28 Member States for the period 1996–2015, this paper confirms the findings of previous studies that the stipulation of fiscal rules reduces fiscal volatility and consequently contributes to macroeconomic stability. Yet, we document that this result only holds for rules which are designed to be unaffected by the current state of the business cycle, i.e. which are "a-cyclical". Those can, for example, be budget balance rules that set ceilings in cyclically adjusted terms. Furthermore, the stringency of fiscal rules makes their stabilising effect more pronounced. Actual compliance with fiscal rules seems to play no systematic role, such that effects of the rules can be observed even if they are not complied with. Overall, our paper suggests that strong, properly designed numerical rules act as an anchor for fiscal policy makers and contribute to more stable discretionary fiscal policy. [ABSTRACT FROM AUTHOR]

In view of the problems of poor correlation and poor calculation accuracy of the existing factors affecting economic fluctuations, this paper designs a new method for analyzing the factors affecting economic fluctuations based on the characteristics of the era of big data. First, after determining the factors influencing the economic fluctuations in the era of big data, the calculation method of key impact indicators is clarified. Then, the entropy law method is used to assign a weight value to the index, and the set is formed after the index is gathered. Then, the EM algorithm is used to assign the expected value to the data in the set. Finally, the set of influencing factors of the economic fluctuations is taken as input information, and the correlation evaluation model of influencing factors of economic fluctuations is constructed by the Monte Carlo method to complete the analysis of the influencing factors. The experimental results show that the correlation coefficient of influencing factors of economic fluctuations in the era of big data analyzed in this paper is high and the calculation accuracy of influencing factors is high, which proves the feasibility of this method. [ABSTRACT FROM AUTHOR]

Economic Brief To what extent do expectations about future productivitydevelopments drive business cycles? Inventories are suitable as a new litmus test toestablish the relevance of expectations in drivingbusiness cycles for two reasons: * Inventories arguably respond strongly to news becauseaccumulating and holding goods for sale is costly andrequires forward planning. * Inventories are one of the key variables behindbusiness cycle fluctuations in the sense that reductionsin the level of goods in stock account for a substantialshare of the decline in GDP during recessions. [Extracted from the article]

In order to explore the impact of the Internet of Things technology on economic market fluctuations and the analysis effect of the Internet of Things technology on economic market fluctuations, this paper uses the Internet of Things algorithm to improve the economic fluctuation model. Moreover, this paper uses the Internet of Things algorithm to locate economic transactions and performs data processing to optimize the intelligent network system to improve the operating effect of the economic system. In addition, this paper improves the sensor node algorithm and proposes to use the weighted value of network node density to balance the positioning problem caused by the unbalanced distribution of network nodes in the detection area. Finally, this paper analyzes the market economy volatility model through the Internet of Things technology, combined with simulation experiments to explore the application of the Internet of Things technology in the economic market volatility model. Through experimental research, it can be known that economic market fluctuation models based on Internet of Things technology can play an important role in market economic analysis. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to analyze the effects of fiscal policy on non-oil GDP within the framework of the Gulf Cooperation Council (GCC) countries. The paper explores asymmetries related to oil price changes (increase vs. decrease) and the state of the business cycle (expansion vs. recession).We used panel structural vector autoregressive (VAR) model, augmented by exogenous 'dummy' variables to estimate fiscal multipliers within a nonlinear framework.The results suggest that (i) linear multipliers are moderate and in line with those found in previous studies; (ii) the multipliers are larger for capital than for current expenditures; (iii) when controlling for oil price changes, the expenditure multipliers are higher during oil market downturns (oil price busts); (iv) spending multipliers are significantly larger when the output gap is negative. The importance of these findings lies on their policy suggestions. These findings indicate that fiscal policy should be designed based on oil price movements and economic fluctuations. [ABSTRACT FROM AUTHOR]

Pointing at the key role digital service innovation plays for the competitiveness of manufacturing firms, they suggest adding digital service innovation as a new type of technological innovation in manufacturing and integrating non-technological service innovations into existing types of marketing (product-service bundling) and organisational (contractual) innovations. Much of the managerial and scholarly attention builds on the premise that servitization, if successfully implemented, can allow firms to achieve (sustainable) growth and higher profitability as compared to their traditional, product-centric business models. Servitization has become one of the most active domains in service research, attracting interests from multiple disciplines, including marketing, operations, service management, engineering management, and strategy. Currently, as exemplified by the papers in this special issue, the servitization studies focus on digitally-enabled and data-driven offerings and business models, service development and innovation, inter-firm and intra-firm relationship dynamics, and performance implications. [Extracted from the article]

Applying VAR/SVAR analysis to the national balance sheet data of the US, this paper provides evidence that the households markedly interact with those of government sectors through the channel of financial leverage, which is defined as the liabilities-to-assets ratio. In particular, the impulse-response and forecasting error decomposition analysis further show that the federal government plays an important role in absorbing the leverage shocks in households. Nevertheless, it should be emphasized that this role of the federal government as somewhat of a macroeconomic stabilizer also costs it heavily in view of its escalating leverage over time. Among other concerns, this highly leveraged financial position renders the federal balance sheet more vulnerable to macro-financial risks, thus reducing the room for manoeuvre for countercyclical policies. Finally, with a relatively low and stable leverage ratio, the state/local governments seem to be less involved in such interactions. However, their prudent balance sheet position also implies that they play a minor role in fiscal measures supporting households during economic downturns. [ABSTRACT FROM AUTHOR]

Under the strategic goal of building a domestic economic cycle, the development quality of social e-commerce in my country needs to be improved urgently. The main reason for the low quality of social e-commerce development in my country is that the natural advantages of social e-commerce, such as high-efficiency dissemination of information and increased consumer utility due to improper sales model design, cannot play a role. However, the lack of research on social e-commerce systems makes it difficult for retailers to obtain effective theoretical guidance for their sales model design. Based on this, this paper takes the three most important and important social e-commerce sales models in my country at present—recommended reward model, online group purchase model, and online crowdfunding model as the research objects, and systematically analyzes the consumer recommendation behaviors in the three sales models. By analyzing and market equilibrium, while improving the theoretical research of social e-commerce, it also provides theoretical basis and policy guidance for the optimal mode design of social e-commerce under different sales modes. This paper considers the consumer recommendation behavior in social networks and analyzes the main characteristics of the three sales models in view of the development status and specific problems of social e-commerce in my country, and then constructs retailer-existing consumer-potential The three-agent dynamic Stackelberg game model of consumers analyzes the influence mechanism and market equilibrium of consumer recommendation behavior under three sales models. [ABSTRACT FROM AUTHOR]

In a model with linear pricing, high-productivity firms charge higher markups and underproduce relative to low-productivity firms. How does declining population growth affect firm dynamics? In contrast, under nonlinear pricing, high-productivity firms still charge higher markups, but underproduction does not happen across firms. But in a world where firms can charge nonlinear prices, this policy would make welfare losses worse, because it would do nothing to address misallocation across consumers within firms. [Extracted from the article]

While isolated episodes of work stoppages keep occurring, aggregate industrial action rates have been on the decline over the last five decades. Attempts to explain this trend centre on the short‐term effects of the business cycle and the long‐term impacts of labour market liberalisation, deindustrialisation and globalisation. This paper argues that household indebtedness is a missing piece of the puzzle. Since indebted employees tend to become self‐disciplined at the workplace on the fear of losing their job and defaulting, this paper argues that the post‐1970 rise of household financialisation is associated with the decline of strike activity. The econometric evidence reported provides strong support to this argument for the cases of Japan, Korea, Sweden, the United States and the United Kingdom over the period 1970–2018. [ABSTRACT FROM AUTHOR]

Based on a Structural VAR approach, we estimated fiscal multipliers for social benefits in Brazil for 1997–2018. Our results suggest that social benefits have relatively large multiplier effects, even when compared to public investment. The multipliers are also larger in the full sample, which includes the country's 2014–16 economic crisis than in the period 1997–2014. In particular, our results show that spending one unit on social expenditures generates a final change in GDP of almost three after two years. The higher estimated multipliers in the full sample appear in the response of household consumption and private investment to shocks in total social expenditures and for different types of social benefits (e.g. cash transfers, unemployment insurance, and pensions). In a context in which the expansion of social protection became prominent as a response to structural changes in the labor market and the Covid-19 pandemic, our paper reinforces its potential role in the short-run economic recovery. [ABSTRACT FROM AUTHOR]

This paper examines the Eurozone (EZ) convergence through Financial and Business cycles frequencies over time. Specifically, I use the Maximum Overlap Discrete Wavelet Transform (MODWT) in order to analyze whether financial cycles on the one hand and business cycles on the other hand are inter-countries synchronized, interconnected, interrelated and co-variant across time and frequencies. I also study if Financial and Business cycles are intra-countries synchronized, interconnected, interrelated, co-variant and phased across time and frequencies. I find that: (i) the EZ is mostly divergent at short term; (ii) the monetary policy led to a boom period between 2002 and 2006 that masked the already existing divergences in the EZ; (iii) that business and financial cycles grew in a case-by-case macroeconomic and financial environment which led to an exacerbation of the divergences; (iv) the lack of synchronization at all frequencies and over time intra-country and inter-country precludes the monetary policy to play its countercyclical role. [ABSTRACT FROM AUTHOR]

This paper supplements a learning‐by‐doing real business cycle model with endogenous organizational forgetting. Empirical evidence shows that the accumulated experience decay rate is not constant over the business cycle, but that forgetting is a function of economic activity. Learning reinforces the effects of productivity shocks, and organizational forgetting exacerbates their impact and increases their persistence. This is of particular interest when a negative productivity shock hits the economy, as the increasing speed of forgetting aggravates the negative shock and delays recovery. [ABSTRACT FROM AUTHOR]

This paper studies the impact of immigration on the US macroeconomy. I identify structural vector autoregressions (SVARs) with time-varying parameters (TVPs) and stochastic volatility (SV) using a novel set of restrictions. The TVP-SV-SVARs are estimated on a quarterly sample including average labor productivity (ALP), hours worked, immigration, consumption, and term spread from 1953 to 2017. An immigration supply shock increases domestic ALP and hours worked over the business cycle horizons. Movements in immigration are explained by its own shock and to a lesser extent by the productivity and news shocks. IRFs driven by these shocks vary over the sample, especially around changes in immigration policy such as the Immigration Act of 1990. In contrast, the forecast error variance decompositions exhibit little change over the sample. Immigration plays an important role in the US macroeconomy. [ABSTRACT FROM AUTHOR]

There has been increasing interest in recent years in monopsony in the labour market. This paper discusses how we can measure monopsony power by combining insights from models based on both frictions and idiosyncrasies. It presents some evidence from the United Kingdom and the United States about how monopsony power varies across the wage distribution within markets, over the business cycle and over time. [ABSTRACT FROM AUTHOR]

Poverty is a global problem, and fighting it is a historical task faced by humanity. The outbreak of poverty crises has a certain cyclicality, and the development of economic research may react to poverty cycles. To validate this view, we take the United States as an empirical example and establish a quantitative research architecture based on the bibliometrics and econometrics. In the first place, we conduct a bibliometric analysis of selected search terms relevant to poverty cycles. After that, the time-series data in the actual economy are collected for reflecting the trends and fluctuations in economic activity affected by poverty cycles. Meanwhile, with both bibliometric and economic data, a detrending measure via the band-pass (BP) filter is performed to estimate cycles. Finally, the Granger causality tests are implemented to explore the interaction between poverty cycles and economic research directly. As a supplement, this paper also provides a quantitative evaluation analysis, namely impulse-response functions, to investigate the influence of economic variables on bibliometric ones. The final results show there indeed exists an impact of poverty cycles in economic activity on relevant discussions in the scientific literature. [ABSTRACT FROM AUTHOR]

This paper provides estimates of the probability of an economy hitting its effective lower bound (ELB) on the nominal interest rate and of the expected duration of such an event for eight advanced economies. To that end, a mean-adjusted panel vector autoregression with static interdependencies and the possibility of regime change is estimated. The simulation procedure produces ELB risk estimates for both the short term, where the current phase of the business cycle plays an important role, and the medium term, where the occurrence of an ELB situation is determined mainly by the equilibrium values of macroeconomic variables. The paper also discusses the ELB event probability estimates with respect to previous approaches used in the literature. [ABSTRACT FROM AUTHOR]

Each individual is unique, and the digital identity associated with a person should model and guarantee this uniqueness and the ability to reliably recognize him/her. In this paper, we review the challenges posed by the sudden transfer of a significant part of the social activity in the online realm, due to the COVID-19 pandemic, with unforeseen consequences on the educational process in particular. If there was a fairly large spectrum of economic activities that were taking place or were facilitated via a digital medium prior to the COVID-19 pandemic, the education system worldwide proved to not have been prepared to provide an effective and consistent response to the going online approach, which was merely a choice, but rather the only embraceable option. In the context of online education, this paper can design a comprehensive and integrated framework for assisting the process of students' digital identity validation, particularly when attending an examination or any other form of academic evaluation conducted remotely. We also consider the integration of digital identity validation with platforms that offer educational content, knowledge evaluation tests, and other elements to which access must be ensured only for authorized users, based on a strict identity identification process to eliminate those who want to defraud or disrupt the functionality of the system. [ABSTRACT FROM AUTHOR]

Purpose: Population ageing will bring economic challenges in the future. The purpose of this paper is to examine whether increased educational level could mitigate the consequences of population ageing on economic sustainability, measured as the gap between labour income and consumption. Design/methodology/approach: Using the National Transfer Accounts (NTA) methodology, the authors decompose labour income and consumption by age and educational level (low, medium and high) and compare obtained age profiles with those calculated conventionally. In addition, using the population projections by age and educational level, the authors project both profiles to 2060 for selected EU countries and assess future economic sustainability. Findings: The results show that the highly educated have a significantly higher surplus for a longer period then those with lower and medium education. Therefore, the improved educational level of individuals will have a substantially positive impact on labour income in the future—on average by about 32% by 2060 for all EU countries included. However, as the better educated also consume more, higher production does not fully translate into improved economic sustainability, but the resulting net effect is still positive at about 19%. Originality/value: The authors present for the first time an NTA by education for 15 EU countries and show the importance of including education in the analysis of the economic life cycle. The authors also show that increased educational level will mitigate the consequences of population ageing on economic sustainability in the future. [ABSTRACT FROM AUTHOR]

We argue that key findings of the empirical literature on the effects of news about future technology—including their tendency to generate negative comovement of macro‐economic aggregates, and their puzzling disinflationary nature—are due to measurement errors in total factor productivity (TFP). In this paper, we estimate the macro‐economic effects of news shocks in the United States using an agnostic identification approach that is robust to measurement errors. We find no evidence of negative comovement conditional on a news shock, and the disinflation puzzle essentially vanishes under our identification strategy. Our results also indicate that news shocks have become an important driver of business‐cycle fluctuations in recent years. [ABSTRACT FROM AUTHOR]

Some financial disruptions that started in California, U.S., in March 2023, resulting in the closure of several medium-size U.S. banks, shed new light on the role of liquidity in business cycle dynamics. In the normal path of the business cycle, liquidity and output mutually interact. Small shocks generally lead to mean reversion through market forces, as a low degree of liquidity dissipation does not significantly disrupt the economic dynamics. However, larger shocks and greater liquidity dissipation arising from runs on financial institutions and contagion effects can trigger tipping points, financial disruptions, and economic downturns. The latter poses severe challenges for Central Banks, which during normal times, usually maintain a hands-off approach with soft regulation and monitoring, allowing the market to operate. However, in severe times of liquidity dissipation, they must swiftly restore liquidity flows and rebuild trust in stability to avoid further disruptions and meltdowns. In this paper, we present a nonlinear model of the liquidity–macro interaction and econometrically explore those types of dynamic features with data from the U.S. economy. Guided by a theoretical model, we use nonlinear econometric methods of a Smooth Transition Regression type to study those features, which provide and suggest further regulation and monitoring guidelines and institutional enforcement of rules. [ABSTRACT FROM AUTHOR]

The primary purpose of this paper is to investigate macroeconomic, financial and welfare effects of financial constraints and policy uncertainty on the economy featuring shifting trend inflation. By developing a New Keynesian model incorporating trend inflation into staggered prices and staggered credit channel, we indicate three important findings. First, we report negligible welfare consequences of financial shocks, whereas policy uncertainty shocks dampen the economic welfare considerably. More importantly, financial frictions are a channel through which policy uncertainty stuns the economy more remarkably. Second, the welfare consequences and business cycles effects of shocks are greater in the high-trend-inflation economy, while the costs of exogenous variations in trend inflation are larger if there is policy uncertainty. Third, among staggered prices and staggered credit, the later plays a more vital role in transmitting adverse effects of shocks to trend inflation into the economy. [ABSTRACT FROM AUTHOR]

This paper sets up a two-agent new Keynesian model to explore the role of financial frictions over the post-war U.S. business cycle. The estimated model via maximum likelihood shows that the share of constrained households which has been substantial since the 1960s has significantly increased during the Great Recession. It also finds that the cost-push shock has been most important in explaining the behavior of the detrended output. The cost-push shock has also played a pivotal role in the fluctuation of inflation during the Great Recession, while the monetary policy shock which has been important in the behavior of inflation before the financial crisis has a negligible role during the Great Recession. [ABSTRACT FROM AUTHOR]

Functional data analysis has significantly enriched the landscape of existing data analysis methodologies, providing a new framework for comprehending data structures and extracting valuable insights. This paper is dedicated to addressing functional data clustering—a pivotal challenge within functional data analysis. Our contribution to this field manifests through the introduction of innovative clustering methodologies tailored specifically to functional curves. Initially, we present a proximity measure algorithm designed for functional curve clustering. This innovative clustering approach offers the flexibility to redefine measurement points on continuous functions, adapting to either equidistant or nonuniform arrangements, as dictated by the demands of the proximity measure. Central to this method is the "proximity threshold", a critical parameter that governs the cluster count, and its selection is thoroughly explored. Subsequently, we propose a time-shift clustering algorithm designed for time-series data. This approach identifies historical data segments that share patterns similar to those observed in the present. To evaluate the effectiveness of our methodologies, we conduct comparisons with the classic K-means clustering method and apply them to simulated data, yielding encouraging simulation results. Moving beyond simulation, we apply the proposed proximity measure algorithm to COVID-19 data, yielding notable clustering accuracy. Additionally, the time-shift clustering algorithm is employed to analyse NASDAQ Composite data, successfully revealing underlying economic cycles. [ABSTRACT FROM AUTHOR]

This paper compares several methods for constructing weekly nowcasts of recession probabilities in Italy, with a focus on the most recent period of the Covid-19 pandemic. The common thread of these methods is that they use, in different ways, the information content provided by financial market data. In particular, a battery of probit models are estimated after extracting information from a large dataset of more than 130 financial market variables observed at a weekly frequency. The accuracy of these models is explored in a pseudo out-of-sample nowcasting exercise. The results demonstrate that nowcasts derived from probit models estimated on a large set of financial variables are, on average, more accurate than those delivered by standard probit models estimated on a single financial covariate, such as the slope of the yield curve. The proposed approach performs well even compared with probit models estimated on single time series of real economic activity variables, such as industrial production, business tendency survey data or composite PMI indicators. Overall, the financial indicators used in this paper can be easily updated as soon as new data become available on a weekly basis, thus providing reliable early estimates of the Italian business cycle. [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 studies how tax‐and‐transfer progressivity influences aggregate fluctuations when interacting with household heterogeneity. Using a simple static model of the extensive margin labor supply, we analytically characterize how a degree of progressivity influences differential labor supply responses to aggregate conditions across heterogeneous households. We then build a quantitative dynamic general equilibrium model with both idiosyncratic and aggregate productivity shocks and show that it delivers moderately procyclical average labor productivity and a large cyclical volatility of aggregate hours relative to output. Our quantitative exercises suggest that progressivity at the bottom of the income distribution shaped by the phasing out of transfers is key for these findings. Finally, we provide suggestive empirical evidence on the heterogeneity of employment responses across the wage distribution. [ABSTRACT FROM AUTHOR]

Capital reallocation between firms is procyclical and leads to variations in measured aggregate productivity. In this paper, we ask how much of the cyclical variation in measured productivity is the consequence of capital reallocation. We build a heterogeneous‐firm model to study the effects of exogenous shocks to total factor productivity (TFP) and to the costs of reallocation. These shocks cause an endogenous cyclicality of measured aggregate productivity. Only a model driven by exogenous TFP shocks is able to generate both data‐consistent cyclical movements in reallocation and sizeable variations in measured aggregate productivity. We find that capital reallocation does not play a major role in amplifying aggregate productivity variations over the business cycle. [ABSTRACT FROM AUTHOR]

The distributed energy system (DES) represents an innovative approach to energy generation and distribution that promotes decentralization and diversification of energy sources. DESs can offer numerous benefits, including increased resiliency, reduced transmission losses, improved efficiency, and lower carbon emissions. The optimal design of a DES requires careful consideration of various factors such as geographical location, climate conditions, and energy demand patterns. This paper utilizes a multi-objective genetic algorithm to optimize the combination of technologies and their corresponding sizes in a distributed energy system for three types of commercial buildings—hospitals, large offices, and large hotels across eight different climate zones in the U.S. A range of technologies are considered for integration into the DES. These technologies include photovoltaic systems, wind turbines, combined heat and power systems, solar thermal collectors, and electrical and thermal energy storage. The two objectives considered are maximizing the reduction in carbon dioxide emissions and minimizing the life cycle costs for the DES. The purpose of this study is to optimize and evaluate the multi-objective design of distributed energy systems aimed at decentralizing and diversifying energy sources. The analysis of optimized DES designs across all 24 case scenarios shows that a balance between cost saving and emission reduction has been achieved. Although this study primarily focuses on specific buildings and climate zones, the methods and findings can be adapted for a wider variety of building types across different geographical locations, thus paving the way for more widespread adoption of optimized distributed energy systems. [ABSTRACT FROM AUTHOR]

The contribution and continuing relevance of Kalecki's paper on 'Political aspects of full employment' on the 80th anniversary of its publication is the central topic. There are five sets of important and interrelated ideas in Kalecki's paper. Full employment was feasible under capitalism from the perspective of securing a high level of demand through government spending. There would be resistance, particularly from business and finance to prolonged full employment, and there are political and social constraints on long-term full employment. Fascism had secured full employment through its relationships with big business and reducing the political obstacles. A political business cycle with full employment achieved at best at the top of the cycle could be generated. The role of 'fundamental reforms' in sustaining full employment under capitalism, and the 'fate' of fundamental reforms is reviewed. [ABSTRACT FROM AUTHOR]

• This paper investigates the predictive ability of oil shocks for international stock market volatility based on a data-rich environment. • We further investigate the predictive ability of the best-performing oil shock by comparing its performance with that of traditional macroeconomic variables and uncertainty. • The LASSO method and regime-switching model can jointly deliver incremental improvement in forecasting accuracy. • This paper tries to provide new evidence for international stock market volatility prediction. This paper investigates the predictive ability of oil shocks for international stock market volatility based on a data-rich environment. Our empirical analysis shows that multiple oil shock measures contain valuable information for predicting stock market volatility, in addition to traditional economic variables and uncertainty indices. Moreover, based on the group 7 countries, the least absolute shrinkage and selection operator method and regime-switching model jointly deliver incremental improvement in forecasting accuracy from both statistical and economic perspectives. These results are confirmed by robustness checks under different business cycles and market conditions, including the COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

This paper applies the hidden Markov switching dynamic regression (MSDR) model to estimate transition probabilities of the Hungarian GDP between recessionary and expansionary periods. The transition probabilities are then compared to the OECD Hungarian binary business cycle indicator to assess the predictive power of the model. The paper proposes a linear model with a mean and a homoscedastic component. The level of symmetricity between the GDP and business cycles is explained by the panel data variables (Unemployment rate, IPI index, Inflation, BUX year-on-year change, and 10-3 Year sovereign bond yield spreads). It is assumed in this paper that by extending the model to encompass an exogenous variable listed in the panel data, essentially making the model bivariate, the maximum likelihood function would capture the business cycle more accurately. The results show that by plugging the unemployment rate as the exogenous variable in the regression, our model's accuracy is 70%. [ABSTRACT FROM AUTHOR]

Several studies have investigated the effect of oil price shocks on business cycles, production, prices, and labour market. The focus of this paper is primarily on the relationship between oil price changes and industrial production in G7 countries. To investigate the heterogeneity of impact, this paper investigates the effects of oil price changes based on the threshold role of net oil exports-to-GDP ratio. A panel smooth transition regression model is employed for analysis over two consecutive periods, namely, 1980–1999 and 2000–2017 as well as the combined period of 1980–2017. The results indicate that oil price hikes have a positive (negative) impact on oil-exporting (oil-importing) countries. The impact appears to be different across time periods, with the 1980–1999 sample exhibiting larger negative impact compared to 2000–2017. This hints on the effectiveness of energy diversification strategies employed post-2000 which resulted in lowering dependence on oil. [ABSTRACT FROM AUTHOR]

Among our findings: * Small firms tend to pledge real estate collateral,medium-sized firms tend to pledge accounts receivablesand blanket liens, and large firms tend raise unsecuredfinancing. Economic Brief We identify the firm-level and aggregate effects ofcollateral price shocks on business lending andinvestment -- also known as the collateral channel-- using detailed bank-firm-loan level data that allow usto observe the pledging of real estate collateral and tocontrol for credit demand and supply conditions. Results We identify the firm-level effects of the collateralchannel conditioning on firm-level demand factors andbank-level supply conditions using detailedbank-firm-loan level data. Instead, most large firms use debt contractsthat are unsecured or based on earnings-based collateral,whose recovery value depends on the continuation value ofthe firm rather than specific assets. [Extracted from the article]

This paper investigates whether business cycles cause financial cycles or vice versa. We also assess whether the US plays a leading role in causing the domestic business and financial cycles of other countries. The literature has established that business and financial cycles are linked through several channels such as credit constraints, the real effects of financial information and the reversal of overoptimistic expectations. Our analysis evaluates the direction of Granger causality using a novel approach based on the mixed-frequency vector autoregression model for the G7 countries. Our approach exploits the fact that real economic activity measured by industrial production is observed at a higher frequency than aggregate credit. We find strong evidence of bidirectional causality between the business and financial cycles, especially in recessions. Furthermore, the US is a global leader since the US business cycle significantly affects other countries' business cycles, especially in terms of expansions. [ABSTRACT FROM AUTHOR]