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This study aims to examine the price and income elasticities of short- and long-run industrial electricity demand in Brazil between 2003 and 2020. The research also examines the impacts of COVID-19 in Brazil’s industrial electricity sector, including an analysis in states more and less industrialized.

Dynamic adjustments models in panel data are used to present robust estimates and analyze the impact of different methodologies on reported elasticities.

The short-run price elasticity is estimated at −0.448, while the long-run values are around −1.60. Regarding income elasticity, the value is 0.069 in the short-run and is concentrated in 0.25 in the long-run. The inelastic results of income show that the industrial demand for electric energy follows the trend of loss of competitiveness of the Brazilian industry in the past years. In addition, the price of natural gas, the level of employment, and, in specific cases, the level of imports also influence industrial electricity demand.

The research is a pioneer in the investigation of the industrial behavior of electricity of the Brazilian industrial branch, using as control variables, the average temperature, and the level of rainfall, this one, so important for a country whose main source is hydroelectric. In addition, to the best of the authors’ knowledge, it is the first study, which is prepared to analyze the effects of COVID-19 on electric consumption in the industrial sector, investigating these impacts, including in the states considered more and less industrialized. The estimates generated may help in the design of the Brazilian energy policy.

Qatar, a wealthy country with an open economy has limited arable land. To meet its domestic food demand, the country heavily relies on food imports. Additionally, the over three year-long economic embargo enforced by regional neighbors and the covariate shock of the COVID-19 pandemic have demonstrated the country's vulnerability to food insecurity and potential for structural breaks in macroeconomic data. The purpose of this paper is to examine short- and long-run determinants of Qatar's imports of aggregate food, meats, dairy and cereals in the presence of structural breaks.

The authors use 24 years of food imports, gross domestic product (GDP) and consumer price index (CPI) data obtained from Qatar's Planning and Statistics Authority. They use the autoregressive distributed lag (ARDL) cointegration framework and Chambers and Pope's exact nonlinear aggregation approach.

Unit root tests in the presence of structural breaks reveal a mixture of I (1) and I (0) variables for which standard cointegration techniques do not apply. The authors found evidence of a significant long-run relationship between structural changes and food imports in Qatar. Impulse response functions indicate full adjustments within three-quarters of a year in the event of an exogenous shock to imports.

An exogenous shock of one standard deviation on this variable would reduce Qatar's food imports by about 2.5% during the first period but recover after the third period.

The failure of past aggregate food demand studies to go beyond standard unit root testing creates considerable doubt about the accuracy of their elasticity estimates. The authors avoid that to provide more credible findings.

This paper aims to examine the dynamics of house prices in metropolitan cities in an emerging economy. The purpose of this study is to characterise the house price dynamics and the spatial heterogeneity in the dynamics.

The author explores spatial heterogeneity in house price dynamics, using data for 35 Indian cities with a million-plus population. The research methodology uses panel econometrics allowing for spatial heterogeneity, cross-sectional dependence and non-stationary data. The author tests for spatial differences and analyses the income elasticity of prices, the role of construction costs and lending to the real estate industry by commercial banks.

Long-term fundamentals drive the Indian housing markets, where wealth parameters are stronger than supply-side parameters such as construction costs or availability of financing for housing projects. The long-term elasticity of house prices to aggregate household deposits (wealth proxy) varies considerably across cities. However, the elasticity estimated at 0.39 is low. The highest coefficient is for Ludhiana (1.14), followed by Bhubaneswar (0.78). The short-term dynamics are robust and show spatial heterogeneity. Short-term momentum (lagged housing price changes) has a parameter value of 0.307. The momentum factor is the crucial dynamic in the short term. The second driver, the reversion rate to long-term equilibrium (estimated at −0.18), is higher than rates reported from developed markets.

This research applies to markets that require some home equity contributions from buyers of housing services.

Stakeholders can characterise stable housing markets based on long-term fundamental value and short-run house price dynamics. Because stable housing markets benefit all stakeholders, weak or non-existent mean reversion dynamics may prompt the intervention of policymakers. The role of urban planners, and local and regional governance, is essential to remove the bottlenecks from the demand side or supply side factors that can lead to runaway prices.

Existing literature is concerned about the risk of a housing bubble due to relaxed credit norms. To prevent housing market bubbles, some regulators require higher contributions from home buyers in the form of equity. The dynamics of house prices in markets with higher owner equity requirements vary from high-leverage markets. The influence of wealth effects is examined using novel data sets. This research, documents in an emerging market context, the observations cited in low-leverage developed markets such as Germany and Japan.

This paper aims to examine whether China's grain price support policy has distorted the grain market price.

The time-varying differences-in-differences (DID) model is used to study the impact of support policies on grain prices, and it is combined with the event study method to explore the dynamic effects of price support policy. Panel data model is used to study the effect of the price support policy on price formation for national grain market prices. In addition, we apply the smooth transformation (STR) model to verify whether there is a distortion in the transmission of grain prices among different markets in China and from the international market to China’s market.

China’s grain price support policy plays a significant role in rising grain market prices, weakens the decisive role of the market mechanism in the formation of grain prices, hinders the spatial transmission of market price signals and decreases the effect of price transmission from the world market to China’s market.

In order to ensure both the stability of grain production as well as the market stability, and also to ensure that intervention policies do not distort the food market, the minimum purchase price of grain and market regulation policies should be adjusted as follows: (1) price support policy should be shifted to an income support policy and (2) reasonably determine the scale of reserves and implement a grain minimum purchase price policy in limited areas.

Our findings are relevant for understanding the effect of China's grain price support policies on the implementation regions and the price transmission effect, which provide reference experience for developing countries to implement food price policies.

This study aims to investigate the impact of local windfall gains from the Spanish Christmas lottery on household consumption behavior.

The study applies differences-in-differences to assess permanent income hypothesis (PIH) validity, examining pre- and postlottery consumption effects. Additionally, it also uses an instrumental variable regression, using the lottery shock as an instrument for total expenditures, to estimate the Engel curves.

The paper finds a PIH violation; households in winning region notably increase consumption on durable and nondurable goods compared to nonwinning ones. Moreover, durable goods consumption is responsive to lottery winnings, while nondurable goods consumption are unit-elastic to expenditure shocks.

To the best of the author’s knowledge, this is the first paper analyzing the effects of winning regions of the Spanish Christmas lottery in all types of consumption goods, testing its consequences in the PIH and estimating its effects in the Engel curves.

This paper aims to examine the effects of the real exchange rate on trade balance in Algeria and investigates whether it represents a viable tool to sustain and improve trade performance using the nonlinear autoregressive distributed lag (NARDL) estimation technique and data from Algeria over the period 1980–2018. This study also highlights the role of trading partners with large income endowments in enhancing the trade balance.

The NARDL model is used to unveil potential short and long run nonlinear responses of the trade balance to shocks in real exchange rates and detect whether these responses are different in terms of sign and magnitude. The paper also provides a dynamic multiplier analysis that tests the existence of a J-Curve pattern in Algeria with several policy recommendations.

The findings confirm the existence of a J-curve pattern in Algeria where domestic currency depreciation will worsen the trade balance in the short run and improve it in the long run. The authors also find that the asymmetrical effect of real exchange rate on trade balance is different in sign and magnitude. Finally, the results indicate that an increase in trade partners' income increases the trade balance in Algeria. The findings are of utmost importance with several policy implications.

While some works investigated the nonlinear response of trade balance to real exchange rate movements, their results remain inconclusive and seem to depend on the characteristics of the country/region of study. Moreover, the role of trade partners and their potential impact on trade balance has been relatively overlooked in the literature. The authors fill this gap by examining the asymmetric impacts of real exchange rate and the effect of trade partners' income on trade balance in Algeria.

This study aims to revisit the empirical debate about the asymmetric relationship between oil prices, energy consumption, CO₂ emissions and economic growth in a panel of 184 countries from 1981 to 2020.

A relatively new research method, the PVAR system GMM, is applied.

The outcome of the PVAR system GMM model at the group level in the study suggests that oil prices exert a positive but statistically insignificant effect on economic growth. Energy consumption is inversely related to economic growth but statistically significant, and the correlation between CO₂ emissions and economic growth is negative but statistically insignificant. The Granger causality test indicates that oil prices, CO₂ emissions, oil rents, energy consumption and savings jointly Granger-cause economic growth. A unidirectional causality runs from energy consumption, savings and economic growth to oil prices. At countries’ income grouping levels, oil prices, oil rent, CO₂ emissions, energy consumption and savings jointly Granger-cause economic growth for the high-income and upper-middle-income countries groups only, while those variables did not jointly Granger-cause economic growth for the low-income and lower-middle-income countries groups. The modulus emanating from the eigenvalue stability condition with the roots of the companion matrix indicates that the model is stable. The results support the asymmetric impacts of oil prices on economic growth and aid policy formulation, particularly the cross-country disparities regarding the nexus between oil prices and growth.

From a methodological perspective, to the best of the author’s knowledge, the study is the first attempt to use the PVAR system GMM and such a large sample group of 184 economies in the post-COVID-19 era to examine the impacts of oil prices on countries’ growth while controlling for other crucial variables, which is noteworthy. Two, using the World Bank categorisation of countries according to income groups, the study adds another layer of contribution to the literature by decomposing the 184 sample economies into four income groups: high-income, low-income, upper-middle-income and lower-middle-income groups to investigate the potential for asymmetric effects of oil prices on growth, the first of its kind in the post-COVID-19 period.

This study aims to determine the export price pass-through elasticity, specifically for Indian exports. It employs static and dynamic panel data techniques to estimate these elasticities. Notably, the pass-through effect is more significant in the long term compared to the short term. The dynamic panel analysis, considering broader economic factors, identifies trade openness and global demand as statistically significant in explaining export price variations. Additionally, the study reveals that the response of export prices to exchange rate changes depends on the nature of those changes, with depreciation having a lesser impact than appreciation. Furthermore, this chapter emphasizes the importance of analyzing these effects at the product level for a comprehensive understanding of the underlying mechanisms. The implications of these findings underscore the crucial role of exchange rates as a policy tool for promoting exports and economic growth, as well as their potential in reducing current account deficits.

COVID-19 has affected the economies adversely from all sides. The sudden halt in production has impacted both the supply and demand sides. It calls for analysis to quantify the impact of the reduction in economic activity on the economy-wide variables so that appropriate steps can be taken. This study aims to evaluate the sensitivity of various sectors of the Indian economy to this dual shock.

The eight-sector open economy general equilibrium Global Trade Analysis Project (GTAP) model has been simulated to evaluate the sector-specific effects of a fall in economic activity due to COVID-19. This model uses an economy-wide accounting framework to quantify the impact of a shock on the given equilibrium economy and report the post-simulation new equilibrium values.

The empirical results state that welfare for the Indian economy falls to the tune of 7.70% due to output shock. Because of demand–supply linkages, it also impacts the inter- and intra-industry flows, demand for factors of production and imports. There is a momentous fall in the demand for factor endowments from all sectors. Among those, the trade-hotel-transport and manufacturing sectors are in the first two positions from the top. The study recommends an immediate revival of the manufacturing and trade-hotel-transport sectors to get the Indian economy back on track.

The present study has modified the existing GTAP model accounting framework through unemployment and output closures to account for the impact of change in sectoral output due to COVID-19 on the level of employment and other macroeconomic variables.

We seek to quantify the relationship between urbanization and economic growth in China using recent advances in econometric techniques.

This study adopts a smoothed instrumental variables quantile regression (SIVQR) estimator to obtain consistent estimates of the effects of urbanization on economic growth in China. Our approach accounts for the differential impacts of urbanization across the conditional distribution of economic growth while allowing for an identification strategy that addresses the endogeneity of urbanization. Our main findings reveal that ignoring urbanization endogeneity leads to inconsistent estimates of urbanization effects. Further, we find a positive relationship between urbanization and growth resembling an inverted U-shape. This supports the hypothesis that the beneficial effects of urbanization intensify at initial stages while diminishing beyond a certain threshold, due perhaps to weakening scale economies.

Our main results indicate that the individual productivity gains brought by urbanization outweigh the negative effects thereof that impede productivity, thus contributing to the economic growth in China. Further, we find that ignoring differential impacts of urbanization underestimates the beneficial effects of urbanization for provinces whose quality of governance is in the vicinity of the center of quality distribution. Ignoring the endogeneity of urbanization generates inconsistent estimates of the elasticity of economic growth with respect to urbanization. Finally, we estimate an inverted U-shape resembling relationship between urbanization and growth.

First, future studies would benefit from incorporating more data as provinces further east on the mainland become more urbanized and urbanization runs its course. Second, controlling the barriers to rural-urban mobility would contribute to the robustness of the estimated relationship between urbanization and growth once such data became available. Unveiling the impact of government-imposed barriers is key to designing optimal policies that help fuel economic growth in the country. Finally, future research could benefit from information on urbanization sources not considered here such as inter-provincial migration, as such data become publicly available.

Quantifying the beneficial effects of urbanization on economic growth can help guide the government in China to further fuel the growth through a set of relevant policy tools that promote urbanization.

Rural-urban migration in China lays the groundwork for economic advancement in recipient cities and economies, as it may induce scale economies. This can benefit both the economy at large and the migrants.

The SIVQR estimator accounts for potential heterogeneous effects of urbanization across the entire conditional distribution of growth while allowing for an identification strategy that addresses the endogeneity of urbanization. An additional distinguishing feature of the current study is our use of the most recent novel, provincial-level data obtained from the National Bureau of Statistics of China. Our focus on a single country allows sidestepping issues arising from the inconsistency of the definition of urban across different countries while accounting for intra-country urbanization drivers intrinsic to China, such as natural features and geographic characteristics. Therefore, our approach has the potential to sidestep the bias resulting from the differences in mechanisms behind urbanization-growth relationships across different countries.