Econometric Estimation Methods Research Articles

Human capital, economic complexity, and ecological footprints: Crafting a sustainable development policy framework for E7 nations

AbstractClimate change is one of the most pressing challenges of our time, with far‐reaching implications for ecosystems, economies, and societies worldwide. Human capital (HUC) and economic complexity (ECC) “understood as structural transformation toward more sophisticated and knowledge‐based production” can be pivotal in curtailing ecological degradation. In this context, the study explores the intricate relationship between HUC, financial development, financial globalization, gross domestic product, ECC, and ecological footprints from 1995 to 2021. To achieve this objective, advanced econometric estimation methods are employed. The results indicate the presence of cross‐sectional dependence and slope heterogeneity in the dataset. The variables present a mixed order of stationarity, while the Westerlund test indicates the presence of a long‐run equilibrium association. The results from the Method of Moments Quantile regression indicate that ECC posed a positive but insignificant effect in the lower quantile (τ = 0.1–0.25), while negative and significant in the middle (τ = 0.50) and upper quantiles (τ = 0.75–0.90). Moreover, financial globalization negatively and significantly affects ecological footprints through all the quantiles except the lower quantile (τ = 0.1). Financial development, gross domestic product, and HUC enhance environmental degradation by escalating ecological footprints. Based on the results, the study suggested enhancing the ECC and financial globalization, while sustainable utilization of HUC and strict regulations for the financial sector to foster sustainable development in E7 countries.

Xtnumfac: A battery of estimators for the number of common factors in time series and panel-data models

In this article, we introduce a new community-contributed command, xtnumfac, for estimating the number of common factors in time-series and panel datasets using the methods of Bai and Ng (2002, Econometrica 70: 191–221), Ahn and Horenstein (2013, Econometrica 81: 1203–1227), Onatski (2010, Review of Economics and Statistics 92: 1004–1016), and Gagliardini, Ossola, and Scaillet (2019, Journal of Econometrics 212: 503–521). Common factors are usually unobserved or unobservable. In time series, they influence all predictors, while in paneldata models, they influence all cross-sectional units at different degrees. Examples are shocks from oil prices, inflation, or demand or supply shocks. Knowledge about the number of factors is key for multiple econometric estimation methods, such as Pesaran (2006, Econometrica 74: 967–1012), Bai (2009, Econometrica 77: 1229–1279), Norkute et al. (2021, Journal of Econometrics 220: 416–446), and Kripfganz and Sarafidis (2021, Stata Journal 21: 659–686). This article discusses a total of 10 methods to estimate the number of common factors. Examples based on Kapetanios, Pesaran, and Reese (2021, Journal of Econometrics 221: 510–541) show that U.S. house prices are exposed to up to 10 common factors. Therefore, when one fits models with house prices as a dependent variable, the number of factors must be considered.

A calendar year mortality model in continuous time

AbstractThis article proposes a continuous time mortality model based on calendar years. Mortality rates belong to a mean-reverting random field indexed by time and age. In order to explain the improvement of life expectancies, the reversion level of mortality rates is the product of a deterministic function of age and of a decreasing jump-diffusion process driving the evolution of longevity. We provide a general closed-form expression for survival probabilities and develop it when the mean reversion level of mortality rates is proportional to a Gompertz–Makeham law. We develop an econometric estimation method and validate the model on the Belgian population.

Balance between Smog Control and Economic Growth in China: Mechanism Analysis Based on the Effect of Green Technology Innovation

The balance between smog pollution (SP) control and economic growth (EG) is currently a major problem facing China's development. Green technology innovation (GTI) is an effective way to promote ecological civilization and realize green development. Thus, whether GTI can facilitate a win-win situation of SP control and stable EG is an important issue of academic concerns. In this paper, the mechanisms of the role of GTI, SP and EG were systematically demonstrated. The corresponding research hypotheses were proposed. Based on the data book of 278 Chinese cities from 2008 to 2020, the effects of GTI on SP and EG were systematically investigated using the econometric estimation method of dynamic spatial panel simultaneous equations. The results show that GTI can reduce SP directly, or indirectly by promoting EG. Although GTI can promote EG, EG may be inhibited due to GTI-induced SP reduction. Inter-regional SP showed significant spatial agglomeration characteristics. EG had significant spatial correlation effects. GTI in neighboring regions can also facilitate local SP control. Further analysis shows that compared with green utility model innovation (GUMI), green invention and innovation (GII) had a more significant effect on reducing SP and promoting EG. In addition, the analysis of the comprehensive effect of GTI on SP and EG shows that GTI can achieve the overall balanced development of SP prevention and EG regardless of GTI types.

Global Structural Shocks and FDI Dynamic Impact on Productive Capacities: An Application of CS-ARDL Estimation

The COVID-19 pandemic has inflicted structural shocks on the global economic system by raising high economic uncertainty. Policymakers are exploring alternative measures and incentivizing foreign direct investment for the restoration of global economic operations to achieve short- and long-term growth. Given this, the study examines the global response of FDI inflow to measure the change in productive capacity. The productive capacity is proxied by structural change, private business sector, institutional quality, transportation infrastructure development, and natural capital. The study implements empirical analysis for a large panel of 170 countries in a data set from 2000 to 2021. Furthermore, the study employed the cross-sectional augmented auto-regressive distributed lag (CS-ARDL) econometric estimation method for better examinations of current changes in an economic outbreak. From the results of the study, the estimations reveal that FDI inward has significant positive impact over the private business sector, institutional quality, transportation infrastructure, and natural capital on inward FDI. In accordance with discussions, the study suggests several pragmatic policy implications to achieve maximum output by utilizing the inward FDI as incentivized by the governments of the selected countries.

Do household energy services affect each other directly? The direct rebound effect of household electricity consumption in Spain

We estimate the magnitude of the direct rebound effect (DRE) of households’ electricity consumption in Spain, through an econometric estimation method of panel data. The results indicate a DRE between 26 and 35% in the short run and around 36% in the long run. Moreover, we find a significant influence of other energy sources that appear to be complementary to electricity consumption according to our estimation. Hence, our results suggest that an improvement in the energy efficiency of an energy service may affect its own energy consumption as well as the energy consumption of other energy services. This would entail a new source of DRE.

Mining, Poverty, and Income Inequality in Central and Eastern European Countries: What Do the Data Tell Us?

The study investigates the effect of mining on both poverty and income inequality in Central and Eastern European countries (CEECs) using econometric estimation methods with panel data spanning from 2009 to 2019. Another objective of this paper was to determine if the complementarity between mining and infrastructural development reduced poverty and or income inequality in CEECs. What triggered the study is the failure of the existing literature to have a common ground regarding the impact of mining on poverty and or income inequality. The existing literature on the subject matter is contradictory, mixed, and divergent; hence, it paves the way for further empirical tests. The study confirmed that the vicious cycle of poverty is relevant in CEECs. According to the dynamic generalized methods of moments (GMM), mining had a significant poverty reduction influence in CEECs. The dynamic GMM and random effects revealed that the complementarity between mining and infrastructural development also enhanced poverty reduction in CEECs. Random effects and pooled OLS shows that mining significantly reduced income inequality in CEECs. However, random effects and the dynamic GMM results indicate that income inequality was significantly reduced by the complementarity between mining and infrastructural development. The authorities in CEECs are therefore urged to implement mining growth and infrastructural development-oriented policies in order to successfully fight off the twin challenges of poverty and income inequality.

Contribution of international tourism to economic growth of Kerala: a subnational-level analysis in India

ABSTRACT The study attempts to understand the contribution of international tourism on economic growth at a sub-national level (i.e. for Kerala) of the Indian economy. By exercising Johansen cointegration test and Vector Error Correction Model on the annual data from 1980 to 2017, it reveals the existence of a positive long-run association between tourism and economic growth. It finds that an increase of Foreign Tourist Arrivals (FTA) by 1% leads to almost a same percentage increase in Gross State Domestic Product (by 0.97%) in the long-run. Thus, it suggests that tourism has a significant potential of unleashing the economic growth of Kerala and this is found to be robust with the use of alternative econometric estimation methods.

Identifying outliers in asset pricing data with a new weighted forward search estimator

ABSTRACT The purpose of this work is to present the Weighted Forward Search (FSW) method for the detection of outliers in asset pricing data. This new estimator, which is based on an algorithm that downweights the most anomalous observations of the dataset, is tested using both simulated and empirical asset pricing data. The impact of outliers on the estimation of asset pricing models is assessed under different scenarios, and the results are evaluated with associated statistical tests based on this new approach. Our proposal generates an alternative procedure for robust estimation of portfolio betas, allowing for the comparison between concurrent asset pricing models. The algorithm, which is both efficient and robust to outliers, is used to provide robust estimates of the models’ parameters in a comparison with traditional econometric estimation methods usually used in the literature. In particular, the precision of the alphas is highly increased when the Forward Search (FS) method is used. We use Monte Carlo simulations, and also the well-known dataset of equity factor returns provided by Prof. Kenneth French, consisting of the 25 Fama-French portfolios on the United States of America equity market using single and three-factor models, on monthly and annual basis. Our results indicate that the marginal rejection of the Fama-French three-factor model is influenced by the presence of outliers in the portfolios, when using monthly returns. In annual data, the use of robust methods increases the rejection level of null alphas in the Capital Asset Pricing Model (CAPM) and the Fama-French three-factor model, with more efficient estimates in the absence of outliers and consistent alphas when outliers are present.

EXPLORING THE MACROECONOMIC DETERMINANTS OF CARBON EMISSIONS IN TRANSITIONAL ECONOMIES: A PANEL DATA ANALYSIS APPROACH

The study's main objective was to investigate the macroeconomic determinants of carbon emissions in transitional economies using panel methods with data ranging from 1996 to 2014. The main data analysis was done using econometric estimation methods such as fixed effects, random effects, pooled ordinary least squares (OLS) and the dynamic generalized methods of moments (GMM) approach whilst robustness tests were done under the umbrella term, the lagged independent variable approach. To a larger extent, infrastructural development, economic growth, trade openness, financial development and natural resources were found to have had a significant positive effect on carbon emissions, in line with major theoretical predictions. On the other hand, renewable energy consumption, foreign direct investment, information and communication technology and human capital development were mainly found to have reduced carbon emissions in transitional economies. The results are firmly supported by literature. Transitional economies are therefore urged to increase their use of renewable energy and information and communication technology (ICT) infrastructure, attract more foreign direct investment (FDI) and implement policies aimed at enhancing human capital development to reduce carbon emissions. Given data availability, future studies must investigate whether other macroeconomic variables mentioned in the empirical literature that they determine carbon emissions are relevant in transitional economies.Keywords: Carbon emissions; Transitional Economies; Panel DataJEL Classifications: P2; P52; B23DOI: https://doi.org/10.32479/ijeep.9362

Determinants of Human Capital Development in Africa

Purpose: The study had two main objectives, namely (1) to investigate the determinants of human capital development and (2) to explore if the complementarity between FDI and information and communication technology-enhanced human capital development in Africa, are in line with theoretical predictions. Design/Approach/Methodology: The study used panel data analysis (fixed effects, random effects, pooled ordinary least squares, dynamic generalized methods of moments) with African panel data ranging from 2001 to 2015. Findings: The dynamic GMM method noted that human capital development was positively affected by its own lag in a significant manner. Under all the four econometric estimation methods, FDI had no significant influence on human capital development, yet information and communication technology significantly impacted human capital development across all the methods used. The study also revealed that the complementarity between FDI and information and communication technology significantly influenced human capital development under fixed effects, random effects, and pooled OLS only. Practical Implications: Africa is urged to implement policies to strengthen ICT implementation to help the inflow of FDI improve human capital development. The study implies that African nations must implement policies to develop their financial sectors if they want to enhance human capital development. Therefore, African countries are urged to increase their expenditure in revamping and strengthening their infrastructure if they wish to enhance the development of human capital. Originality/Value: This paper is unique because it is the first of its kind to investigate the impact of the complementarity between FDI and information and communication technology on human capital development and to consider the dynamic features of human capital development data.

Analysis of the Determinants of Export Diversification in the Franc Zone: A Comparative Study in WAEMU and CAEMU Countries

The objective of this study is to analyze the determinants of export diversification in the 14 countries of the Franc Zone and compare them between WAEMU and CAEMU zones. Export diversification leads to sustainable economic growth, a satisfactory balance of payments, job creation and income redistribution. To this end, the study uses Bruno (2005a, b) LSDVC econometric estimation methods over the period 1990-2015 to identify factors that may or may not improve export diversification in these countries. The main lesson of this study is that more factors favor diversification in WAEMU countries compared to those in the CAEMU zone. In addition, we note a U-inverse relationship between per capita income and diversification in the WAEMU zone while a U-shaped relationship is observed in the second zone. Moreover, the results on the Franc Zone as a whole show that the most relevant explicative factors of export diversification are: human capital, economic development, financial liberalization, degree of trade openness, public investment and the index of democracy.

The determinants for a circular economy in Europe.

The circular economy contrasts with the traditional linear economy since it presents a sustainable way both to produce goods and services and to contribute to the development of economies. This paper aims to contribute to a better knowledge of the efficiency of resources productivity, a common indicator to compare how circular economies are, through the estimation of the main determinants for the circular economy in Europe. A systematic analysis and comparison of the performance of all the European Union countries was performed to get further insight into their root causes and to help designing future policies towards a more circular European Union economy. With this purpose, a set of determinant factors for a circular economy in Europe were analysed, under the period between 2000 and 2016. A cluster analysis was applied and complemented with three econometric estimation methods: panel unit root tests, panel cointegration tests and vector autoregression model. The main findings allowed to cluster European countries into three different groups according to the growth rate of their resources productivity and to explain them according to the selected exploratory factors. Special efforts were made to explain the highest productivity growth group, as a way to find relevant drivers towards sustainable productivity growths.

The gravity model of trade

Purpose. The purpose of this study is to trace the theoretical developments of the gravity model of trade. The key question is: what are the dominant features of the development of the gravity trade model? Methodology. This research is conducted by employing a number of methods that include the historical, descriptive and analytical methods. The main contribution of this paper is to trace the historical and theoretical development phases of the gravity model. Findings. This study is a novel attempt in terms of the identification of the four distinctive phases of the development of the gravity model. This work would, therefore, expand the existing literature on the gravity model. We argue that the development of the gravity model is the outcome of many research efforts. A large body of literature has given the model a solid theoretical foundation. But there is no consensus about the proper econometric estimation methods of the model. The gravity model is significant both historically and analytically. It is a useful tool for the analysis of international trade. It has become a popular research device used by the researchers and policy makers around the world. The gravity is regarded as one of the most successful models in the literature of international economics. Originality. The original contributions of this paper lie in streamlining the consistent historical development of the gravity model over a longer period of time-frame, ranging from 1885 to 2018. Limitations and Implications. This work is theoretical aspects of the trade gravity model. Future researchers could overcome the limitations by combining the theoretical and empirical studies in a paper. This paper can help the future researchers in dealing with the broad body of literature of gravity model. Acknowledement. This study was supported by the National Natural Science Foundation of China (grants No.71673223 & 71473197), and a PhD scholarship from the China Scholarship Council (CSC). The first author would like to thank the CSC for the financial support. He also acknowledges the invaluable research advice and guidance received from Dr. Yoto V. Yotov, professor at the School of Economics of the Lebow College of Business at Drexel University, Philadelphia, USA. The authors are highly grateful to the anonymous reviewers, managing editor, and the editor-in chief for their kind help and critical comments on the earlier drafts of the paper. However, the authors are responsible for the contents and limitations of the study. They declared no conflict of interests.

Can economic and environmental benefits associated with agricultural intensification be sustained at high population densities? A farm level empirical analysis

Boserup’s pioneering theory holds that rising population density can be accompanied by sustainable agricultural intensification. But can this positive relationship be sustained indefinitely, or are there conditions under which rising population density can lead to declining agricultural productivity? This study utilizes survey data on farm households in Kenya and soil samples on their main maize plots to assess whether Boserupian agricultural intensification is sustainable at high population densities. The study employs econometric estimation methods to assess the effect of land management practices and population density on soil quality and then determines the effect of soil quality on crop productivity. Results show evidence of endogenous sustainable agricultural intensification accompanied by improvements in soil quality and crop yields at low population densities. However, as population densities exceed roughly 600 persons/km2, we observe a deterioration in indicators of soil organic and reactive carbon, soil pH, and plant available phosphorous. Deterioration in soil quality leads to binding nutrient constraints associated with reduced crop yield response to inorganic fertilizer application that further reduces crop productivity. These results raise the specter of unsustainable forms of agricultural intensification associated with deteriorating soil capital, and point to the imperative of identifying and implementing effective strategies for increasing farmers’ use of sustainable land management practices in rural areas facing already high and rising population densities.

Corporate social responsibility and financial performance in Saudi Arabia

Purpose The purpose of this paper is to investigate the impact of corporate social responsibility (CSR) on corporate financial performance (CFP) using Zakat as a measure for CSR. Design/methodology/approach The study examines a sample of 107 non-financial firms listed on the Saudi Arabia stock market over a ten-year period from 2004 to 2013. The authors use the generalized method of moments framework developed by Arellano and Bover (1995) and Blundell and Bond (1998). In addition, for comparison purpose and as a robustness check, the present study uses other panel data techniques including fixed effects model, random effects model (and pooled ordinary least squares. Findings The results reveal that there is a strong positive relationship between CSR (Zakat) and CFP. This suggests that Zakat contribute positively to both firm’s profitability and value and can be considered as a win-win strategy to maximize returns and improve performance while considering the society as a whole. The results are robust to alternative econometric estimation methods. Practical implications The companies in Islamic economies can effectively and efficiently implement the basic Shari’a Law of paying Zakat, as a successful measure to implement CSR program, thus benefiting the society by narrowing the gap between the haves and have-nots, that, in turn, leads the company to achieve successfully its short-term as well as long-term goals and enhances the value of the firm in the market. Moreover, corporations are generally encouraged to adopt CSR because of its perceived benefits to both macro- and micro-performances. Originality/value To the best of the author’s knowledge, this is the first empirical study attempting to examine CSR-CFP relationship within Saudi context employing Zakat as a proxy for CSR. Additionally, the paper provides support for the stakeholder theory from an Islamic perspective.

The environmental Kuznets curve model for greenhouse gas emissions in Canada

Abstract This paper tests for the applicability of the Environmental Kuznets Curve (EKC) hypothesis at the Canadian and provincial/territorial levels using greenhouse gas emissions as an indicator for environmental degradation. The hypothesis is tested using provincial and territorial panel data from 1990 to 2014. The results vary depending on the econometric estimation method. The pooled regression results are mixed, with the EKC hypothesis confirmed at the Canadian level and in half of the provinces and territories. However, the fixed-effects regression results confirm the EKC hypothesis at the Canadian level and in all provinces and territories. The results also highlight the significance of technological change and province/territory specific characteristics in determining the level of greenhouse gas emissions.

Ex Post State Aid Evaluation in Environmental Aid

The obligation to carry out an ex post evaluation of certain State aid measures was introduced in the European Union in 2014. This obligation represents an important element of the broader State Aid Modernisation initiative of DG Competition. In this article, we offer guidance, both from a legal and an economic perspective, on when an ex post evaluation is required, which methods are available and which methods are actually considered by Member States. More specifically, we propose a ‘traffic light system’, supporting a self-assessment of whether an ex post evaluation is required for a specific measure or not. Furthermore, we review the 24 evaluation plans which were approved by the European Commission by August 2018, with respect to the proposed approaches to the measurement of direct and indirect effects, appropriateness and proportionality. We find that the most common method considered by Member States in their evaluation plans is the econometric estimation of differences-in-differences. Keywords: State aid ex post evaluation; Environmental aid; Econometric estimation methods; Evaluation plans.

THE DETERMINANTS OF OIL DEMAND: EVIDENCE FROM ITALY

The main purpose of this paper is to estimate price and income elasticities of crude oil demand in the Italian economy between 1975 and 2014. The Bound Test is employed as an econometric estimation method. According to Bound Test result, a cointegration relationship has been found between oil consumption, oil prices, and real income. Empirical findings show that the long-run income elasticity and price elasticity of oil demand are statistically insignificant in Italy. In addition, price and income elasticities of oil demand estimated as negative-inelastic and positive-inelastic in the short run, respectively. Thus, crude oil can be defined as a necessity good for Italian consumers over the short term. Also, Error Correction Term (ECT) is estimated to be -1.18. According to ECT, a deviation from the long run equilibrium level of oil demand is corrected about one year later. Italy is an energy dependent country and imports most of it. Since crude oil is necessity, the government should diversify energy sources which are consumed in the entire country and/or undertake policies to increase energy efficiency.

Understanding the relationship between health and internal migration in the United Kingdom

Purpose Studies on the relationship between migration and health status of individuals most often concentrate on international migrants. In contrast, the purpose of this paper is to examine the relationship between health and internal migration using the first 18 waves of the British Household Survey. Design/methodology/approach The authors use the 12-version of General Health Questionnaire (GHQ), an indicator of mental health, and physical health indicators as the health variables. This study uses different econometrics estimation methods in modelling the relationship in order to address omitted variable bias as well as unobserved heterogeneity. The econometric estimation methods include Pooled OLS, random effects (RE), fixed effects (FE) and then probit RE. The authors explore the relationship by comparing the health status of movers and non-movers and different types of internal migration such as between local authority districts and between regions. Findings The results of this research suggest that there is healthy migrant effect on migration within UK on some indicators of physical health like arm/leg, heart and migraine/headache problems, but not on mental health indicator. And the effects are similar for both males and females. It is advised therefore that the department of health should improve the health of those affected by these ailments so that they can have a chance to move perhaps to better their lots. Originality/value This study uses different econometrics estimation methods in modelling the relationship in order to address omitted variable bias as well as unobserved heterogeneity. The econometric estimation methods include Pooled OLS, RE, FE and then probit RE.