Econometric Procedures Research Articles

The day-of-the-week-effect on the volatility of commodities

The volatilities of oil, gold, silver and the energy sector have recently become products that can be traded, and investors have begun using them for hedging and speculation. Our extensive analysis of the daily prices of these volatility products documents significant and non-random patterns of movement on Mondays and Fridays. These patterns are stable in terms of the percentage of times in which they occur and the magnitude of the returns. The results are robust using different subsamples and econometric procedures. Finally, we develop a trading rule involving investing in the differentials that results in sizeable abnormal returns. Our results have far reaching implications for the pricing of volatility products.

Socio-economic Determinants of Maternal Healthcare Behaviour: Evidence from Pakistan

Maternal healthcare behaviour is a complex behavioural phenomenon. Studies refer to maternal healthcare behaviour as a determinant of individual, household and social factors such as accessibility, affordability and awareness regarding health care. Using the Pakistan Demographic and Household Survey, 2012-13, the study aims to identify the socio-economic determinants of maternal healthcare behaviour of women in Pakistan. Women’s health is a neglected area of study in Pakistan; particularly at household level thus this study will provide an insight into this sensitive area. Empirical estimation is carried out through simple econometric procedure. The econometric specifications followed in the study identify the potential variables that could influence pre and postnatal healthcare behaviour of women in Pakistan. The estimates of this analysis depict that mother’s predisposing factors such as educational level, previous fetal loss experience; spousal educational attainment and economic status are important determinants of maternal health behaviour (MHB) in Pakistan.

Trade impacts of the New Silk Road in Africa: Insight from Neural Networks Analysis

The Belt and Road Initiative (BRI) is aimed to strengthen the preferential reciprocal trade between China and the Belt-Road nations. Quantitative evaluations of BRI to determine whether it can explicitly provide more insight into China’s bilateral trade among its partners are needed. Hence, improving prediction accuracy while using more superior algorithms for sustainable decision-making remains essential since decision-makers have been interested in predicting the future. Machine learning algorithms, such as supervised artificial neural networks (ANN), outperform several econometric procedures in predictions; therefore, they are potentially powerful techniques to evaluate BRI. This study uses detailed China’s bilateral export data from 1990 to 2017 to analyze and evaluate the impact of BRI on bilateral trade using gravity model estimations and ANN analysis techniques. The finding suggests that China’s bilateral export flow among the BRI countries results in a slight increase in inter-regional trade. The study provides a comparison view on the different estimation procedures of the gravity model – ordinary least squares (OLS) and Poisson pseudo-maximum likelihood (PPML) with the ANN. The ANN associated with fixed country effects reveals a more accurate estimation compared to a baseline model and with country-year fixed effects. Contrarily, the OLS estimator and PPML showed mixed results. Grounded on the study dataset, the ANN estimation of the gravity equation was superior over the other procedures to explain the variability of the dependent variable (export) regarding the prediction accuracy using root mean squared error (RMSE) and R-square.

Primena dinamičkih modela u procenjivanju odnosa između direktnih poreza i investicija u OECD zemljama

The article researches the direct tax effect on investment share in thirty-five OECD countries for the period from 1996 to 2016 year. The goal of this research is to determine how direct taxes influence on investment level measured by the share in the gross domestic product. The empirical analysis enables the implementation of fundamental econometric procedures as well as different dynamic panel models in order to measure effect of direct taxes. Results of Hausman show that PMG model is appropriate for measuring the effect of tax revenue growth, personal income tax, corporate income tax and property tax on investment share in selected countries. The model results reflect significant effect of tax revenue growth, personal income tax and property tax in the long term, while corporate tax is not significant for investment share in OECD countries. However, direct taxes do not have significant impact on investment share in the short-term, except tax revenue growth has positive effect on the investment in observed period.

A multi-sectoral balance of payments constrained growth approach with intermediate imports: The case of Nigeria

This study seeks to ascertain whether the Multi-Sectoral Balance of Payments Constrained Growth model is suitable to explain Nigeria's growth experience from 1981 to 2018. The paper explicitly incorporates the effects of intermediate imports and relative prices into the analysis. We employ the autoregressive distributed lag econometric procedure for the analysis. The outcome of the study shows that the Multi-Sectoral Balance of Payments Constrained Growth model correctly predicts Nigeria's growth path. It was found that manufactured export is one of the main determinants of the intermediate import demand function. Considerable reliance on this type of import to produce final exports could reduce the gains from trade, thus adversely affecting the GDP growth of the economy compatible with the BoP constrained growth model in the long run.

Dynamics of Public Debt Sustainability and Economic Growth: The Case of Sri Lanka

Over the past decades, most of the developing nations in the world have to face a critical issue of rising public debt. In Sri Lanka, public debt has increased to a higher level during the post liberalization period. Debt can be influenced economic growth and general welfare of the public only it is used properly without transferring additional burden on public. Therefore, it is beneficial to evaluate the short run and long run effect of debt on economic growth and its sustainable level. Hence, this study examines the dynamics of debt sustainability and the impact of public debt on economic growth in Sri Lanka using annual time series data for the period 1960-2018. This study uses deductive research approach and the model framework develops based on the literature. This study adopts econometric procedures to find out the short run and long run effect of internal and external public debt on economic growth in Sri Lanka and the sustainability of public debts analyze using graphical analysis with the support of the past literature. The econometrics procedure follows unit root test, co-integration tests and vector error correction mechanism together with granger causality test to investigate short run and long run effects of debt on growth. Empirical findings of the study revealed that internal and external public debt has positive impact on economic growth in the long run confirming crowding in effect of investment. Further, Gross domestic capital formation and government expenditure has positive impact on economic growth in the long run. The coefficient of Error Correction Term (ECT) suggests disequilibrium in the real GDP growth is corrected at the speed of 58 percent annually confirming the existence of long run relationship between debt and growth. Granger causality test confirmed uni-directional causality running from real economic growth to internal public debt in Sri Lanka. The sustainability of public debt in Sri Lanka is not in a good position as most of such measures reflect unfavorable trend over the last period. Finally, the finding of the study is useful to the policy makers to design and implement appropriate policies to achieve desired level of economic growth for the country.

Influence of food safety standards on trade: Evidence from the pistachio sector

AbstractThis paper analyses the influence of food safety standards related to aflatoxin contamination on the pistachio trade of the world's two leading pistachio producers (the United States and Iran) during the period 1996–2014. Using diverse econometric procedures, the estimation of extended gravity models shows that both countries benefit from stricter food safety standards imposed by importing countries. The results also show that US exports are not negatively affected by the distance from the importer (higher differentiation), while the impact of distance on the Iranian pistachio trade is negative. The results reveal that stricter food safety requirements are positive for both producing countries, regardless of their level of economic development, resulting in a “win–win” scenario. However, the findings also confirm that other variables, such as distance, the role of producers' associations and quality perception, should be considered. [EconLit citations: F10, F63, I18, Q17].

A unified measure of Fed monetary policy shocks

We develop a U.S. monetary policy shock series that stably bridges periods of conventional and unconventional policymaking, is largely unpredictable, and contains no significant central bank information effect. We attribute differences between our measure and often-used alternatives to our econometric procedure, a partial least squares approach, and our using the full maturity spectrum of interest rates in estimating the shock. We find that shocks to our monetary policy series have particularly large effects on maturities in the middle of the term structure and produce conventionally-signed impulse responses of output and inflation.

Mobile money system and market risk mitigation: an econometric case study of Kenya's farm business

PurposeThe study presents and evaluates a proposition that there is market information bundled with the mobile money (m-money) system. Also, that such information is disseminated to farmers in the process of their normal financial transactions and business interactions. This market information is important to mitigate the price uncertainty of farm products.Design/methodology/approachThe empirical analysis is conducted with a two-stage econometric procedure. First, a probit model is used to estimate the likelihood of m-money take-up by farm entrepreneurs. Second, the ordinary least squares model is used to regress the farming price uncertainty index on the m-money take-up, which is quantified with a set of predicted values from the probit model in the first stage. The data used in econometric estimation come from Kenya's FinAccess Household Survey published in 2016.FindingsThe results of this paper show a negative effect of m-money service take-up on the price uncertainty index. A one unit increase in the m-money system is associated with a 12% reduction in the price uncertainty index. The authors interpret this as saying that access to the m-money system by farm business has a beneficial spillover effect on product risk mitigation, ceteris paribus.Research limitations/implicationsThe implication of this research is that policy initiatives which support farm entrepreneurs to access the m-money system should be encouraged not only for their financial inclusion advantage but also for their positive externality on product risk amelioration for rural farm businesses.Originality/valueThe paper introduces an idea that the m-money system is bundled with relevant information for mitigating price risk to the benefit of rural farm businesses.

Does globalisation alleviate polarisation?

AbstractIn this study, we investigate the effects of globalisation on polarisation in a panel data set of 149 countries between 2000 and 2017. We consider the Revisited KOF Globalisation indices and two measures of polarisation: polarisation of society and political polarisation. The findings show that globalisation decreases polarisation. We also separate de jure and de facto measures of globalisation and observe significant suppressing effects of the de facto and de jure indices of globalisation on both indicators of polarisation. In addition, we find that economic and political globalisation measures are negatively related to polarisation indicators. The baseline findings are robust to estimate different models and to use different econometric procedures. Finally, we address potential issues with endogeneity, omitted variable bias, outliers and reverse causality.

Time-varying monetary policy reaction function under asymmetric preferences: revisiting the Brazilian inflation targeting experience

PurposeThis paper analyzes the potential presence of time-varying asymmetries in the preference parameters of the Central Bank of Brazil during the inflation targeting regime.Design/methodology/approachGiven the econometric issues inherent to classical time-varying parameter (TVP) regressions, a Bayesian estimation procedure is implemented in order to provide more robust parameter estimates. A stochastic volatility specification is also included to take into account the potential presence of conditional heteroskedasticity.FindingsThe obtained results show that the reduced form and structural parameters were not constant during the period considered. Moreover, the subsequent analysis of the preference parameters provided evidences of short periods in which asymmetry was an important feature to the conduction of monetary policy in Brazil. Yet, during most of the sample period, the loss function was considered to be symmetrical.Originality/valueThis paper aims to contribute to the rather scarce monetary debate on time-varying central bank preferences. The study of Lopes and Aragón (2014) is, to the best of the authors’ knowledge, the only study for Brazil considering specifically TVPs. The authors applied Kalman filter estimation to data from 2000:M1 to 2011:M12. Despite the similar structure of TVPs, the present paper extends the latter study by controlling for stochastic volatility. Ignoring conditional heteroskedasticity might lead to spurious movements in time-varying variables and inaccurate inference (Hamilton, 2010). Thus, the stochastic volatility specification is included to take this issue into account. The authors follow the theoretical scheme put forward by Surico (2007) and Aragón and Portugal (2010), in which the economy is modeled from a New Keynesian perspective and the central bank loss function is assumed to be asymmetric regarding the responses to inflation and output deviations from their targets. On the empirical side, the authors propose a TVP univariate regression with stochastic volatility for the Brazilian reduced-form reaction function, following closely the Bayesian econometric procedure developed by Nakajima (2011). Given the nonlinear non-Gaussian nature of the TVP regression with stochastic volatility, the choice of a nonlinear Bayesian approach using the Markov chain Monte Carlo (MCMC) method is justified due to the intractability of the associated likelihood function (Primiceri, 2005). Finally, based on the theoretical model specification, the authors intend to recover the central bank preference parameters as to further evaluate the degree of asymmetry and its potential time-variation under the inflation targeting regime.

Economic growth in China and its impact on international commodity prices

AbstractSince the turn of the century, China has experienced economic growth that has called for rapid industrialisation, infrastructure growth and urbanisation, making China highly dependent on primary commodities. The resource intensive growth path followed by a slowdown in recent years has raised the question to what extent her demand for commodities can affect international commodity prices. To this end, recent studies have analysed the link between economic growth or slowdown on commodity prices using linear multivariate models. However, a problem is that commodity prices are known to be highly variable and characterised by multiple structural changes. With such characteristics of the data, it is likely to be the case one may obtain mis‐specified inferences from a linear multivariate framework. Accordingly, we make use of novel Flexible Fourier Form (FFF) econometric procedures to account for multiple breaks in the economic variables, which have better power and size properties over the standard linear models. We find that the persistence of economic variables employed in this study and their causal link are better approximated by such nonlinear FFF procedures. Our results show that there is evidence of short run predictability between selected commodity prices and economic growth in China. Further, the responses of different commodity prices to shocks in economic growth are quite profound especially for those cases where we find causal links with economic growth in China. While we find a significant impact of economic growth of China on commodity prices, the response varies for different commodities.

The interplay between knowledge-based competitiveness, people's good health and well-being: new empirical evidence from Central and Eastern European countries.

The enhancement of countries’ competitiveness represents an essential credential in current economic interventions, national policy frameworks and strategies, mainly in relation to sustainable economic development. This paper explores the drivers of competitiveness in Central and Eastern European Countries (CEECs) in the knowledge economy, and its further impact on economic welfare, with a particular focus on individuals’ perceived good health and well-being (a good predictor of people’s future use of the healthcare system and mortality risk and a benchmark for sustainable development). The dataset grasps 11 CEECs analyzed during the 2000–2018 lapse of time. The methodological endeavor is based on three econometric procedures encompassing macroeconometric models, structural equation modelling (SEM) and network analysis through Gaussian Graphical Models. Main findings entail that CEECs competitiveness is driven by the key coordinates of the knowledge economy, particularly tertiary education, employment in technology and knowledge-intensive sectors, and additional government financial support dedicated for research and development activities. Moreover, in a further complex setting, competitiveness increases under the impact of education, research, development and innovation leads to significant upwards in GDP per capita levels. However, the further linkages with individuals’ good health and well-being, when considered as a consequence of welfare increase following knowledge-driven competitiveness, or as a direct impact of competitiveness increases, entail a downsized outcome in terms of individuals’ perceived health. Our results provide solid grounds for the development of new tailored policies designed to enhance CEECs knowledge-driven competitiveness in a comprehensive framework, with benefit spillovers on sustainable economic development.Electronic supplementary materialThe online version of this article (10.1007/s11135-020-01015-4) contains supplementary material, which is available to authorized users.

Diversifying with Cryptocurrencies during COVID-19

Literature suggests assets become more correlated during economic down- turns. The current COVID-19 crisis provides an unprecedented opportunity to investigate this considerably further. Further, whether cryptocurrencies provide a diversification for equities is still an unsettled issue. Additionally, the question of whether cryptocurrency futures are safe havens has received very little attention. We employ several econometric procedures, including wavelet coherence, copula principal component, and neural network analyses to rigorously examine the role of COVID-19 on the paired co-movements of six cryptocurrencies, as well as bitcoin futures, with fourteen equity indices and the VIX. We nd co-movements between cryptocurrencies and equity indices gradually increased as COVID-19 progressed. However, most of these co-movements are positively correlated, suggesting that cryptocurrencies do not provide a diversification benefit during downturns. Exceptions, however, are the co-movements of bitcoin futures and tether being negative with equities. Results are consistent with investment vehicles that attract either more informed or more speculative investors dierentiating themselves as safe havens.

Social, economic and family factors associated with binge drinking in Spanish adolescents

BackgroundThe main aim of this study was to determine the socioeconomic and family factors associated with binge drinking (BD) in Spanish adolescents who participated in a web-based computer intervention for the prevention of binge drinking known as Alerta Alcohol.MethodsLongitudinal analyses were carried out in a sample of Andalusian adolescents aged 15 to 19 enrolled in public schools, which was part of a two-arm cluster randomized controlled trial with an intervention group (IG) who received the Alerta Alcohol programme and a control group (CG) who did not receive any active intervention. Panel count data and the following econometric procedures were used: negative binomial, a two-part model and a finite mixture model. The endogenous variable in all models was the number of BD occasions in the last 30 days. A total of 1247 subjects in the pre-intervention period, with an average age of 16.8 years, plus 612 adolescents in the follow-up period (4 months later), were included in the analysis.ResultsIn relation to findings, being older (≥ 17 years old), having more pocket money and higher family alcohol consumption were associated with greater BD. By contrast, subjects who completed the questionnaire on Wednesday, Thursday or Friday, further from the previous weekend, indicated a lower number of BD occasions.ConclusionsOur results suggest the need to include families, especially parents and siblings, in interventions aimed at preventing alcohol use among adolescents, given the association shown between BD and both family alcohol consumption and weekly pocket money or availability of money to adolescents. Given the findings with regard to age, future research aimed at intervening in early adolescence to prevent BD would be justified.Trial registration(ClinicalTrials.gov): NCT03288896. Registration date: September 20, 2017. “Retrospectively registered”.

Competition and invention quality: Evidence from Swiss firms

Existing literature investigates the effect of access to international markets on the technological activities of companies neglecting the issue of competition. It is not only the access to such markets, but in particular the competition in these markets that drives technological activities. This partly explains the divergent findings in the literature. We try to fill this research gap by investigating the relationship between competition in international technological markets, invention quality, and firm performance. We compile a unique time-series cross-section dataset combining patent and survey data covering the period 1990–2013. The survey data are based on stratified random sample of about 6000 companies drawn from the census data provided by the Swiss Federal Statistical Office. This data allows us to develop composite indicators for competition and invention quality, giving credit to their versatile features. We apply econometric procedures using international trade shocks as an instrument to identify invention quality and address selection issues with a Bayesian imputation approach. We find evidence that the positive effect of invention quality on domestic sales of innovative products is positively mediated by intensive competition in international markets. This has important implications for trade policy and underscores the meaningfulness of open markets for invention quality.

Revisiting the Dynamics of Tourism, Economic Growth, and Environmental Pollutants in the Emerging Economies—Sustainable Tourism Policy Implications

Tourism contributions to economic growth and well-being have been widely acknowledged; however, its impacts on the environment demand an integrated approach to policy improvement across institutions in the emerging economies for the development of sustainable tourism practices. This study investigates the causal relationship between tourism, economic growth (GDP, capital investment), energy consumption, and environmental pollutants in developing economies, explicitly focusing on the case of Pakistan. Various econometric procedures and techniques were applied to test the proposed hypotheses. The findings suggest that economic growth support tourism development. Tourists’ arrivals have a significant positive impact on energy consumption, capital investment, and CO2 emissions; besides, environmental pollutant (CO2) causes negative effects on tourism. The results suggest that a 1 unit increase in tourism increases CO2 emissions metric tons per capita by 0.26 units in the long-run. A 1 unit increase in capital investment increases CO2 emissions metric tons per capita by 0.21 units, and a 1 unit increase in energy consumption increases CO2 emissions metric tons per capita by 0.51 units in the long-run. In the short-run, a 1 unit increase in tourism, capital investment, and energy consumption rises CO2 emissions metric tons per capita by 0.045, 0.04, and 0.08 units, respectively. Sustainable tourism remains a sole option in developing economies to enhance the competitiveness of tourism as a tool for friendly developments. Thus, tourism policies are needed to be integrated with overall economic, environmental, and energy policies to encourage the shift towards sustainable tourism development to minimize environmental pollution.

Irrelevance of inflation: The Dow stocks

The irrelevance of inflation is a proposition, inherited from corporate finance, which states that inflation is irrelevant for the valuation of nominal and real stock prices. In other terms, Net Present Values (NPVs) and stock returns are independent of the inflation rate. The issue at stake is both theoretical and empirical, although the first came much before the latter. In the empirical realm, stock returns are found to be statistically negatively related to inflation. However, and theoretically, the classical school predicted that they should be related positively one-to-one. Moreover long run analysis, that came later, found that stock prices are positively related to price indexes. This stems from the fact that stocks are claims upon real assets, and, therefore, should be a hedge against inflation with the same one-to-one relation. This paper differs by subjecting all these hypotheses to the individual stocks included in the Dow Jones Industrial Index, and not to returns calculated from stock indexes, which is the usage. The empirical results in this paper support strongly the irrelevance of inflation. This is true whatever the price index, whatever the econometric procedure, whatever the industry to which the stock belongs, and whatever the specification of the model. Hence inflation is neither negatively nor positively related to stock returns, whether nominal or real.

Rate-optimal estimation of the Blumenthal–Getoor index of a Lévy process

The Blumenthal–Getoor (BG) index characterizes the jump measure of an infinitely active Lévy process. It determines sample path properties and affects the behavior of various econometric procedures. If the process contains a diffusion term, existing estimators of the BG index based on high-frequency observations achieve rates of convergence which are suboptimal by a polynomial factor. In this paper, a novel estimator for the BG index and the successive BG indices is presented, attaining the optimal rate of convergence. If an additional proportionality factor needs to be inferred, the proposed estimator is rate-optimal up to logarithmic factors. Furthermore, our method yields a new efficient volatility estimator which accounts for jumps of infinite variation. All parameters are estimated jointly by the generalized method of moments. A simulation study compares the finite sample behavior of the proposed estimators with competing methods from the financial econometrics literature.

Impact of Population Growth, Poverty and Unemployment on Economic Growth

This research explores the impact of population growth, poverty and unemployment on economic growth in Nigeria using Auto Regressive Distributed Lag (ARDL). The study employed an econometric procedure; unit root test which involved the use of Augmented Dickey Fuller test (ADF) and Phillip-Perron test (PP). The cointegration test technique used in the study is Auto Regressive and Distributed Lag (ARDL). The study variables are real GDP, population, poverty, unemployment and foreign direct investment has control variable. The null hypothesis stated that there is presence of a unit root was failed to be rejected at levels but rejected at first difference according to the two tests (ADP and PP) employed. The study found that some of the variables are stationary at level I(0) while others are stationary at first difference I(1).The results of the cointegration test showed that there exist cointegrating equation between explanatory variables and economic growth. The ECT speed of adjustment to the normal equilibrium confirms their long run relationship of the variables. Finally, the study found that population and FDI have a positive impact while poverty and unemployment has negative impact on GDP. Based on these findings recommend that policy makers should grow the real economic sectors to improve and enhance productivity, exports, job creation, curb inflation and reduce poverty and rapid economic growth and substitute the non-productive imports with domestic products and develop enabling environment to attract foreign private investors.