Consumption Volatility Research Articles

Macroeconomic volatility and terrorism incidents in Africa

AbstractThis article investigates the impact of macroeconomic volatility on terrorism in 38 African economies spanning the period from 1980 to 2012, using available data. It examines four categories of terrorism markers: domestic, transnational, uncertain, and total, and their correlation with the volatility of four macroeconomic indicators—inflation, output growth, domestic credit to the private sector, and government expenditures. The study employs the negative binomial regression estimator on both the conditional variance structures of the generalized autoregressive conditional heteroskedasticity (GARCH) and exponential GARCH (EGARCH) and the unconditional measure of a 3‐year interval time varying of measuring macroeconomic variables' volatilities on other regressors. I find, first, that inflation volatility is a significant predictor of all terrorism markers, except for transnational terrorism. This implies that high inflation volatility is linked to increased domestic terrorism. Second, the role of domestic credit to the private sector in mitigating transnational terrorist activities highlights the importance of stable private sector access to credit in reducing such incidents. Third, government consumption expenditure volatility has a dual effect on terrorism: it amplifies domestic terrorism but serves as a mitigating factor for total terrorism. This indicates that stable government expenditure can reduce overall terrorism, but might increase domestic terrorism. Last, other variables—such as population, ethnicity, conflicts, surface areas, and lagged terrorism values—are also found to influence the examined terrorism measures. For robustness, I employ alternative statistical techniques, including Poisson Pseudo‐maximum likelihood (PPML) estimation with multiple high‐dimensional fixed effects (HDFE). In summary, this study emphasizes the critical role of addressing inflation volatility in macroeconomic policies as a primary measure to counter terrorism. Stable economic conditions, particularly in relation to inflation, can significantly contribute to reducing terrorism in African economies.

Space–Time Forecasting of Heating & Cooling Energy Needs as an Energy Poverty Measure in Romania

Lack of access to basic energy services, known as energy poverty, remains felt in the country, with seasonal changes and an economic divide. The frameworks to measure energy poverty differ spatially and temporally, with climate change and behavioral culture being the essential influencing factors. This paper is focused on heating and cooling energy demands, which can be defined as an energy poverty metric for the propensity to be at risk of energy poverty caused by climate regime. Employing sophisticated statistical space–time forecasting tools, we build a model incorporating spatial and temporal energy consumption volatility across Romanian regions at the NUTS3 level. The model considers climatic conditions and raw data from 45 years (1979–2023) of cooling and heating degree days to determine local trajectories for the next nine years. Identifying high-energy-poverty-risk areas in our research can provide valuable insights for policymakers, enabling them to develop targeted plans for eliminating energy poverty and ensuring equitable access to heating and cooling. The results underline the necessity of differentiated approaches in energy policies and add value to the general understanding of energy poverty issues and conditions, considering the Romanian climatic and socio-economic context.

Consumption dynamics with law of small numbers

We propose an intertemporal consumption-saving model by exploring the implications of the Law of Small Numbers (LSN), a belief heuristic stating that any sample realization of a population should be representative of the population. First, the existence of the LSN reduces the precautionary savings demand. More importantly, we show that the LSN belief structure provides an alternative explanation for two fundamental anomalies in consumption theory: (1) excess sensitivity by showing that past changes in income predict future changes in consumption; and (2) excess smoothness by lowering consumption volatility and generating the empirical magnitude.

Disaster learning and aggregate investment

We extend a production-based asset pricing model by introducing learning about disaster risk. The information is not perfect, and Bayesian learning is adopted to update beliefs about the likelihood of rare disasters. We show that disaster learning reconciles key stylized facts about macroeconomic quantities and financial markets. For macroeconomic quantities, during the crisis, the decline in aggregate investments is much worse than that of output, whereas the decline in aggregate consumption is moderate relative to that of output. Additionally, the model endogenously features lower consumption volatility and higher investment volatility than that of output. For financial markets, belief updating over a rare disaster produces a higher equity premium, lower risk-free rate, and more volatile stock returns. Finally, we show that jump intensity uncertainty accounts for a substantial fraction of the total welfare cost of rare disasters.

The impact of air pollution on household vulnerability to poverty: An empirical study from household data in China

Understanding the relationship between air pollution and poverty is essential for improving livelihoods and fostering common prosperity. While existing studies have concentrated on the impact of extreme climate and natural disasters on poverty, the adverse effects of air pollution are neglected. Using the China Family Panel Studies (CFPS) from 2016 to 2018, this study investigates air pollution's effect on household vulnerability to poverty, including the mechanisms and heterogeneity. Results shows that air pollution significantly heightens household vulnerability to poverty. This effect stems from air pollution lowering incomes and increasing healthcare burden. Heterogeneity analysis shows that air pollution negatively impacts households with low wealth, poorly educated, weak social networks, and those in developing, non-coastal, and high-terrain cities. Furthermore, air pollution more severely affects households with high consumption volatility and low wealth compared to those with low vulnerability. We also discover that the adverse effects of air pollution on household vulnerability to poverty diminish with increased physical capital. Local governments are encouraged to intensify efforts in reducing emissions through improved environmental regulations, protecting residents from pollution-induced harm.

Household Consumption and Dispersed Information

By introducing an information friction to a heterogeneous agent model, we are able to explain two patterns of small economies experiencing large income changes: (1) excess volatility in consumption and (2) household consumption elasticities that have low correlation with income. With a standard dispersed information structure, households cannot distinguish aggregate income shocks from idiosyncratic ones. Their consumption responds excessively to aggregate shocks, which they incorrectly forecast to be too persistent. This effect occurs homogeneously across the income distribution, lowering the correlation of the consumption elasticity with income. We corroborate our central mechanism using survey data on household expectations of their future earnings.

Consumption smoothing or consumption binging? The effects of government-led consumer credit expansion in Brazil

Brazil initiated a major credit expansion program through government banks in 2011. The program primarily targeted public sector workers with offers of payroll-backed loans. Using individual-level administrative data we find that the program led to a 15 percentage point rise in debt to initial income for public sector workers. We develop a new method for estimating workers' expected income growth, and show that “consumption smoothing” cannot explain the rise in consumer borrowing. Instead, the evidence supports “consumption binging”: less financially sophisticated workers borrowed more at high real interest rates, and experienced both higher consumption volatility and lower average consumption.

Media governance and fiscal expenditure volatility—evidence from China

ABSTRACT This study examines the impact of media governance on fiscal expenditure volatility, using China’s television governance as an exogenous shock. We find that media governance can significantly reduce fiscal expenditure volatility. Moreover, we also analyse the mechanism and heterogeneity of government quality in causal effects. Our findings suggest that media governance significantly improves government quality. In regions with lower levels of government integrity or more efficient fiscal governance, media governance has a more significant stabilizing effect on fiscal expenditure.

The Rationality Bias

AbstractWe analyze differences in consumption and wealth in an estimated New Keynesian model with rational and boundedly rational households. Shocks are shown to cause consumption and wealth heterogeneity due to the “rationality bias” of boundedly rational households. This bias can be decomposed into three components, which, for certain specifications of monetary policy, can exactly offset each other. Moreover, a more hawkish response to inflation leads to more volatility in consumption and wealth heterogeneity, which makes it optimal for the central bank to set lower coefficients in the Taylor rule than would have been the case under homogeneous rational expectations.

Housing, Distribution, and Welfare

AbstractHousing is a long‐lived asset whose value is sensitive to variations in expectations of long‐run growth rates and interest rates. When a large fraction of households has leverage, housing price fluctuations cause large‐scale redistribution and consumption volatility. We find that a practical way to insure the young and the poor from the housing market fluctuations is through a well‐functioning rental market. In practice, homeownership subsidies keep the rental market small and the housing cycle affects aggregate consumption. Removing homeownership subsidies hurts old homeowners, while leverage limits hurt young homeowners.

Exploring the impact of digital inclusive finance on consumption volatility: Insights from household entrepreneurship and income volatility

The application of digital technology has reshaped all aspects of social life, and the impact of financial technology on the economy is unprecedented. Consumption is an eternal issue in economic development; however, most existing studies have concentrated on how digital inclusive Finance affects household consumption levels, giving little attention to consumption volatility. Nonetheless, policies that overlook consumption volatility are less likely to achieve societal welfare goals, particularly in developing countries. This study aims to fill this gap and unveil the “black box” of the impact of digital inclusive Finance on consumption volatility, which can benefit the development of economic resilience. Utilizing data from the China Household Finance Survey, our research assesses the impact of digital inclusive Finance on household consumption volatility and discovers that digital inclusive Finance significantly smooths out these fluctuations. Mechanism tests further indicate that the main transmission channels for this impact are promoting entrepreneurship and reducing income volatility. Moreover, heterogeneity tests show that the effect of digital inclusive Finance in smoothing household consumption volatility is more pronounced in households with sound financial standing, higher financial literacy, and internet access, especially in rural areas. These findings enrich the literature on digital inclusive Finance's role in managing volatility and extend the theory on the inclusive nature of digital inclusive Finance, offering valuable practical implications for developing countries.

Consumption Volatility Risk: Does It Really Matter?

Consumption Volatility Risk: Does It Really Matter?

The impact of digital financial development on the green economy: An analysis based on a volatility perspective

Without a doubt, green development is a consensus reached by most countries globally. However, detailed discussions on the impact of digital finance on green development remain scant among scholars. To address this gap, we first construct a Green Development Index for China. Utilizing provincial panel data from 2011 to 2019, we aim to evaluate the influence of digital finance on green development. Additionally, our research aimed to ascertain the ‘rebound’ effect of digital finance on green development, especially in terms of volatility. The results show that the development of digital finance has a positive impact on green development, but this impact is asymmetric, mainly exhibiting regional disparities and threshold effects. Moreover, digital finance can effectively suppress consumption volatility and the negative impact of green financial shocks on green development. Importantly, the smoothing effect of digital finance is particularly pronounced during downturn phases of the financial cycle. Further examination revealed the moderating roles of educational attainment, economic structure, R&D, and governmental intervention. Our findings underscore the pressing need for governmental authorities to prioritize economic transformation and R&D activities to amplify the synergistic benefits between digital finance and green growth. Concurrently, it's essential for governments to carefully evaluate their fiscal policies to ensure they do not inadvertently obstruct the path to sustainable green development.

STGNet: Short‐term residential load forecasting with spatial–temporal gated fusion network

AbstractWith the continuous transformation of the global power system, ensuring the flexibility and stability of the power system has become a direction that the global energy industry has been striving for. This puts forward higher requirements for load forecasting, especially high‐precision short‐term residential load forecasting. However, the high volatility and uncertainty of electric consumption make this problem challenging. Existing methods usually focus on capturing temporal correlations and ignore the underlying spatial correlations in historical loads, which is crucial for accurate forecasting. In this paper, we propose a novel spatial–temporal gated fusion network (STGNet) for short‐term residential load forecasting including not only individual residential load but also aggregated load. By seeking both adaptive neighbors and temporal similarity neighbors, we construct a dynamic graph based on a data‐driven method. On this basis, we provide an adaptive graph gated fusion mechanism to capture fine‐grained node‐specific spatial dependence more accurately and comprehensively. Finally, a bidirectional gated recurrent unit (BiGRU) is utilized to learn the temporal dependence of load data. Extensive experiments on real‐world datasets are conducted and demonstrate the superiority of STGNet over the existing approaches.

Navigating geopolitical crises for energy security: Evaluating optimal subsidy policies via a Markov switching DSGE model

This paper aims to provide insights on the design of optimal subsidy policies to enhance energy security amidst energy disruptions triggered by geopolitical conflicts. We introduce a novel Markov switching dynamic stochastic general equilibrium (MS-DSGE) model to address the limitations of existing integrated assessment models in environmental evaluation. These models often fail to adequately consider the environmental and economic impacts of geopolitical conflicts and do not prioritize energy security sufficiently in policymaking. Our application of the MS-DSGE model to the Russia–Ukraine conflict reveals significant decreases in output, social welfare, and energy consumption during disruptions. The mere anticipation of an energy crisis influences household behaviors, leading to a reduction in energy, output, and consumption volatility, while concurrently increasing volatility in social welfare. We show that an optimal subsidy policy should be contingent upon productivity levels, energy imports, and the economy’s responsiveness to economic shocks. Moreover, the policy should also be adaptable to prevailing economic conditions and the likelihood of an upcoming crisis.

Satellite forecasting of crop harvest can trigger a cross-hemispheric production response and improve global food security

Global food security is increasingly threatened by climate change and regional human conflicts. Abnormal fluctuations in crop production in major exporting countries can cause volatility in food prices and household consumption in importing countries. Here we show that timely forecasting of crop harvest from satellite data over major exporting regions can trigger production response in the opposite hemisphere to offset the short-term fluctuations and stabilize global food supply. Satellite forecasting can reduce the fluctuation extents of country-level prices by 1.1 to 12.5 percentage points for anticipated wheat shortage or surplus in Russia and Ukraine, and even reverse the price shock in importing countries for anticipated soybean shortage in Brazil. Our research demonstrates that by leveraging the seasonal lags in crop calendars between the Northern and Southern Hemispheres, operational crop monitoring from satellite data can provide a mechanism to improve global food security.

Optimal GDP-indexed bonds

I investigate the introduction of GDP-indexed bonds as an additional source of government borrowing in a quantitative default model. The idea of linking debt payments to developments in GDP resurfaced with the 1980s debt crisis and peaked with the COVID-19 outbreak. I show that the gains from this idea depend on the underlying indexation method and are highest if payments are symmetrically tied to developments in GDP. Optimized indexed debt can eradicate default risk, halve consumption volatility, and increase asset prices while raising the government's debt balances. These changes occur because an optimally chosen indexation method does a better job at completing the markets.

Does financial inclusion promote consumption smoothing? Evidence from emerging and developing economies

An important issue for emerging and developing economies (EMDEs) is how to reduce the occurrence of hand-to-mouth consumption by allowing consumption smoothing. Financial inclusion increases access to the formal banking system and financial markets, and allows households to use more appropriate financial instruments, which should enable them to diversify consumption, disrupting the connection to idiosyncratic income shocks. This paper empirically investigates whether financial inclusion can smooth consumption and promote risk sharing for a large heterogenous sample of 85 EMDEs for 1995 to 2017. We find that financial inclusion decreases the volatility of consumption and reduces deviations in country consumption vs world consumption. Curiously, we find that financial inclusion does not help countries improve risk sharing by lowering their exposure to idiosyncratic output shocks. We further find that risk sharing through domestic credit markets expands with financial inclusion, although it does not appear to reduce unsmoothed consumption.

How does excessive volatility of consumption vary across countries?

I revisit the excess volatility of the consumption puzzle, a feature often observed in developing and emerging economies. I assess how the excess volatility of consumption varies across countries by incorporating interrelation between countries’ commodity dependence and income level. This is estimated in the context of the excess sensitivity of the consumption to output using cross-country panel data. I find that the sensitivity of consumption on the income level appears differently by the country’s commodity dependence. The sensitivity is higher in low-income groups for the commodity-dependent countries, whereas the opposite pattern is observed for non-commodity-dependent countries.

Currency concentration in sovereign debt, exchange rate cyclicality, and volatility in consumption

For emerging economies, borrowing abroad is a double-edged sword: it can buffer against adverse economic shocks and smooth their domestic consumption; however, it can also amplify volatility in consumption, depending on the currency in which the debt is denominated and cyclicality in the borrower’s exchange rate. We empirically investigate the nexus among external debt portfolios, exchange rate cyclicality, and volatility in consumption of low- and middle-income countries. Since 1980, many countries have concentrated their external debt portfolios’ currency composition. By constructing debt-weighted effective exchange rates, we find that currency concentration magnifies exchange rate pro-cyclicality, making domestic consumption more volatile when national income fluctuates. Our results endorse diversifying the currency composition of external debt to mitigate the negative consequences of “original sin.”