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Brazil uses the dollar as a vehicle currency to invoice its exports. This fact produces a tendency toward equalizing the prices of products in dollars in the international market and reducing the ability of firms to practice pricing-to-market (PTM). This study aims to evaluate the hypothesis by estimating error correction models in panel data, obtaining estimates of PTM for 25 manufacturing products exported by Brazil between 2010 and 2020.

This study uses the correlated common effect estimator proposed by Pesaran (2006) and Chudik and Pesaran (2015b) to estimate the PTM coefficients.

Results of this study indicate that exporters practice local-currency pricing stability for dollar prices. This study obtains that Brazilian exporters tend to stabilize their dollar price for exports, reducing heterogeneity between destination markets. The results are in agreement with the hypothesis of the prevalence of the coalescing effect of Goldberg and Tille (2008) and lower sensitivity of the markup adjustment to the specific market, as pointed out by Corsetti et al. (2018). The pricing of Brazilian exports in dollars reflects a profit maximization strategy that considers an international price system based on global demand for products.

In addition to analyzing the dollar role in the pricing of Brazilian exports through the triangular decomposition, this study also shows the importance of examining the cross-section dependence of errors, considering the heterogeneous cointegration in export pricing models and producing PTM estimates for short-term and long-term.

The purpose of this study is to examine how renewable energy consumption moderates the relationship between inequality and carbon dioxide (CO₂) emissions for Brazil, Russia, India, China and South Africa (BRICS). The nexus between energy use and geopolitical tensions has also been explored.

This study has used distinctive data sets from 1990 to 2018 to explore the interconnections on emission, energy use, inequality and geopolitics. To do away with the difficulties related to heterogeneity and cross-sectional dependence (CD), this paper uses recent estimation methods that are robust to panel heterogeneity and CD.

The results of the panel augmented mean group (AMG) estimation and common correlated effects mean group (CCEMG) estimation verify the environmental Kuznets curve. The findings show that a 1% rise in Gini inequality leads to a 0.24% rise in the CO₂ emission (AMG) method and a 0.17% rise in emissions CCEMG (method). As far as the moderating impact of renewable energy upon Gini measure of inequality is concerned, it is −0.10 AMG and CCEMG methods of estimation, respectively. However, the moderating impact of renewable energy on the geopolitical index leads to a mitigating impact on CO₂ emissions, 0.55% decline in AMG method.

This research makes a distinctive contribution by investigating for the first time to the best of the authors’ knowledge the main pillars of sustainable ecological development in the context of the BRICS nations.

The purpose of this paper is to find the effects of human capital inequality on economic growth.

Thailand Labor Force Survey has been used to generate provincial average years of schooling and Gini coefficient of years of schooling for the years 1995‒2012. Econometric techniques have been employed to identify the effects of human capital inequality on economic growth.

Economic growth is inversely affected by the distribution of human capital in Thailand. The coefficient of human capital inequality suggests that if Gini coefficient increases by 0.01 points, gross provincial product (GPP) decreases by about 2 percentage points in the long run. However, the effect of average years of schooling in GPP is not significant.

There is a lack of strong theoretical background for the relationship between human capital inequality and economic growth to support the empirical study.

The findings of the study help to design and evaluate education policies in developing countries like Thailand and other low- and middle-income countries.

This paper is among the first attempts to analyze the effect of human capital inequality on economic growth with sub-national level annual data. In addition, it considers cross sectional dependence in panel model.

This paper studies the dynamics and elasticities of house prices in Spain and Portugal (Iberia) at the Metropolitan Statistical Area (MSA) level, addressing panel regression problems such as heterogeneity and cross-sectional dependence between MSA.

The authors develop a two steps study. First, five distinct estimation methodologies are applied to estimate the long-term house price equilibrium of the Iberian MSA house market: Mean Group (MG), Fully Modified Ordinary Least Square (FMOLS) MG (FMOLS-MG), FMOLS Augmented MG (FMOLS-AMG), Common Correlated Effects MG (CCEMG) and Dynamic CCEMG (DCCEMG). FMOLS-AMG is found to be the best estimator for the long-term model. Second, an additional five distinct estimation methodologies are applied to estimate the short-term house price dynamics using the long-term FMOLS-AMG estimated price in the error-correction term of the short-term dynamic house price model: OLS Fixed Effects (FE), OLS Random Effects (RE), MG, CCEMG and DCCEMG. DCCEMG is found to be the best estimator for the short-term model.

The results show that in the long run Iberian house prices are inelastic to aggregate income (0.227). This is a much lower elasticity than what was previously found in US MSA house price studies, suggesting that there are other factors explaining Iberian house prices. According to our study, coastal MSA presents an inelastic housing supply and a price to income elasticity close to one, whereas inland MSA are shown to have an elastic supply and a non-significant price to income elasticity. Spatial differences are important and cross-section dependence is prevalent, affecting estimates in conventional methodologies that do not account for these limitations, such as OLS-FE and OLS-RE. Momentum and mean reversion are the main determinants of short-term dynamics.

Recent econometric advances that account for slope heterogeneity and cross-section dependence produce more accurate estimates than conventional panel estimation methodologies. The results suggest that house markets should be analyzed at the metropolitan level, not at the national level and that there are significant differences between short-term and long-term house price determinants.

To the best of the authors' knowledge, this is the first study applying recent econometric advances to the Iberian MSA house market.

This study aims to investigate the effects of flight delays, distance, number of passengers and seasonality on revenue in the Turkish air transport industry.

The domestic return routes of a Turkish airline company were examined to address this issue. Among five cities and six airports, 14 major domestic return routes were selected. The augmented mean group (AMG) estimator and common correlated effects mean group (CCEMG) estimator were conducted with a two-way fixed effects (FE) robustness test in this study.

The results show that arrival flight delay and departure flight delay had negative effects on revenue, whereas the distance between airports, the number of air passengers and seasonality had positive effects on revenue.

The data used in this study were retrieved from a Turkish airline company; for future research, other airline companies operating in Turkey may be included.

These findings could be evaluated by air transportation leaders to provide a guide to make strategic decisions to achieve greater performance in this competitive environment.

The originality of the paper comes from the facts that besides distance and number of passengers, the authors control for the seasonality when assessing the effects of flight delay on revenue; they use panel data techniques, which permit them to control for individual heterogeneity, and create more variability, more efficiency and less collinearity among the variables; they use two recent panel data techniques, CCEMG and AMG, allowing for cross-section dependence.

The purpose of this study is to revisit the twin deficit hypothesis (TDH) and provide insights into the transmission mechanism connecting budget deficits and current account deficits for five major South Asian countries, namely, India, Bangladesh, Pakistan Sri Lanka and Nepal for the period 1985-2016.

This study uses a multivariate framework including real interest rate, real exchange rate and real gross domestic product to avoid the possibility of incorrect inferences caused by omission of relevant mediating variables. The long-run relationship and causality are investigated through the autoregressive distributed lag bounds testing approach and Toda Yamamoto approach, respectively, for each individual country. The robustness of the results is assessed with the help of Westerlund’s cointegration test and group mean fully modified ordinary least squares (GM-FMOLS), group mean dynamic ordinary least square (GM-DOLS) and common correlated effect mean group (CCEMG) estimators in the panel framework.

Both time series and panel evidences indicate long-run relationship between budget balance (BB) and current account balance (CAB) together with the mediating variables. The results indicate bi-directional causation between the two balances for India and Bangladesh, TDH for Pakistan and Sri Lanka and the reverse causation from CAB to BB for Nepal. Regarding the transmission mechanism, the results indicate the absence of the causal chain postulated by Mundell–Fleming, which predicts that BB causes CAB via interest rate and exchange rate. A CCEMG estimate of the import demand function reveals a positive government spending elasticity of imports suggesting that BB affects CAB by direct impact through demand.

This study augments the twin deficit literature on South Asian countries by providing insights into the transmission mechanism connecting the BB and CAB. Moreover, the study provides robust evidences on the TDH by using both time series and panel data techniques.

The study's objective is to examine the relevance of globalization in affecting the size of the shadow economy in selected African nations.

To do this, the authors employ the KOF globalization index and implement both static and dynamic common correlated mean group estimators on a panel of 24 African nations from 1995–2017. This technique accommodates the issue of cross-sectional dependence, sample bias and endogenous regressors. Panel threshold analysis is also conducted to establish the nonlinearity between globalization and the shadow economy. To examine the causality between the variables, the study employs Dumitrescu and Hurlin's panel causality test.

The results show that globalization reduces the size of the shadow economy. The results of the nonlinear analysis suggest a U-shaped relationship. Overall globalization has a threshold impact of 48.837%, economic globalization has 45.615% and political globalization has 66.661% while social globalization has a threshold value of 35.744%. The results of the panel causality show that there is a bidirectional causality between the two variables.

The results suggest that the government and other relevant authorities need to introduce capital controls and other policy measures to moderate the degree of social, political and cultural diffusion. Appropriate policies should be formulated to monitor the extent of African economic openness to other continents to maximize the gains from globalization.

Apart from being the first study in the African region that evaluates the relevance of globalization in controlling the shadow economy, it also analyzes the dynamics and threshold analysis between the two variables using advanced panel econometrics which makes the study unique. The study suggests that globalization tools are useful for affecting the size of the shadow economy in Africa. This study provides fresh empirical evidence on the impact of globalization on the shadow economy in the case of Africa.

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 the impact of information and telecommunication technologies (ICT-proxied by mobile phone subscription and Internet usage) on carbon dioxide (CO2) emissions in the Organization for Economic Cooperation and Development (OECD) countries from 1990 to 2018.

The Cross-section Autoregressive Distributed Lag (CS-ARDL) model is employed to address the potential cross-section dependence problem. Common Correlated Effects Mean Group (CCEMG) and Augmented Mean Group (AMG) estimators are used to test for robustness of results.

Results reveal contrasting effects of mobile phone subscription and Internet usage on CO2 emissions. While mobile phone penetration helps mitigate CO2 emissions, Internet usage tends to increase the emissions. Findings show that renewable energy is beneficial to the environment while economic growth is harmful to the environment. The effects of financial development and trade openness seem negligible.

This study offers practical implications for policymakers. As different proxies of ICT could have contradictory impact on CO2, governments should be cautious against utilizing ICT to mitigate CO2. Findings point to the benefits of renewable energy in alleviating CO2 emissions. Therefore, governments are strongly advised to implement policies facilitating renewable energy consumption.

Previous studies ignored the problem of cross-section dependence which could lead to biased results and cause misleading inferences. This study aims to fill this void in the literature.

The purpose of this paper is to investigate the problem of fiscal sustainability for a panel of developing Asian economies.

In this study, cross-section dependence and heterogeneity are controlled while estimating the fiscal reaction function, which shows how governments react to the accumulation of public debt. The study employs the common correlated effects mean group estimator in Pesaran (2006) for a panel of 22 developing Asian economies for the period 1999‒2017.

It is found that the fiscal sustainability issue in the region is not so benign as in previous studies. Overall, fiscal policy is unsustainable, even for the nonlinear fiscal rule. Country-specific long-run coefficients are also examined in the study.

The findings show that many developing economies in the region could not satisfy the intertemporal budget constraint, which raises concerns about debt sustainability in the area, especially for the post-crisis period.

This study investigates whether governments can maintain the sustainability of public finances in the long-run, if the ratios of public debt over GDP and primary deficit over GDP continue their recent problematic trends. Another novelty is controlling for heterogeneous effects among the countries in the region to give a more precise picture of debt sustainability. The empirical evidence also supports that insolvency risk can occur at low levels of public debt.