Economic Growth and Dynamic Panel Model

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Public Debt and Economic Growth nexus: A Dynamic Panel ARDL approach

Public Debt and Economic Growth nexus: A Dynamic Panel ARDL approach

There are three theoretical viewpoints that explain the public debt and economic growth nexus. The first school of thought is known as the Keynesian hypothesis. Through an Investment Savings-Liquidity Preference Money Supply (IS-LM) model Keynesian economists illustrate that there is a positive association between debt and growth. They demonstrate that public debt induced by a debt-financed fiscal policy leads to an expan- sionary effect on the economy. In fact, these theorists argue that budget deficits lead to an increase in aggregate demand. This in turn generates higher levels of income and trans- actions demand for money and prices. In light of these economic factors, interest rates rise prompting higher levels of savings and investment (Van and Sudhipongpracha, 2015). Nevertheless, this positive impact can only be triggered if the finance obtained from pub- lic borrowing runs in parallel with productive government spending including investing in infrastructure, health and education.

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The Oil, Government’s Budget and Economic Growth: A Dynamic Panel Data Model for Selected Oil Exporting Economies

The Oil, Government’s Budget and Economic Growth: A Dynamic Panel Data Model for Selected Oil Exporting Economies

All estimations of control variables have expected signs and almost all of them are significant. Lag of GDP growth has positive significant (except for model 6) effect on GDP growth. It seems that as the number of independent variables increases, the significance level (P- Value) of this estimator is increased too. Variable 𝑙𝑛𝑔𝑑𝑝 𝑡−1 as the measure of initial national income has negative significant effect on economic growth that implies convergence. Inflation has negative effect on economic growth that maybe is a result of high rates of inflation in some of these countries; however this estimation is not significant. Two last variables, Gross Capital Formation as a

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Taxation and Economic Growth : An Empirical Analysis on Dynamic Panel Data of WAEMU Countries

Taxation and Economic Growth : An Empirical Analysis on Dynamic Panel Data of WAEMU Countries

dummies variables : apart from the model variables, six dummies temporal variables (dumpt1, dumpt2, dumpt3, dumpt4, dumpt5 and dumpt6) and eight dummies individual variables (dumdev , dumbur91, dumcd98, dumcd10, dumma92, dumnig92, dumsen99 and dumtg91) have been introduced in the model. The dummies temporal variables are introduced in the model because on the six periods, the first is not taken in account in the regressions for the presence of the lagged dependent variable. The variables dumtp1, dumtp3 and dumtp6 appear in the first estimation while dumtp2, dumtp3, dumtp4 and dumtp5 in the second. The reasons of the introduction of the dummies variables in some studies on the WAEMU countries are limited. According to Nubukpo (2007), apart from the boom beginning of the raw materials (Niger in 1973-1975, Ivory Coast in 1975), the dryness that Senegal knew in 1973-1974, the policies crisis (Benin in 1989, Togo in 1993) and the change of the franc CFA party in 1994, it is the beginning of the public finance cleansing process with the structural adjustment programs adopted by the countries of the Union in the beginning of 1980 (between 1979 and 1983) which explains the presence of dummies variables in some estimations. By another way, the policy unrest in Mali (1991-1992) and in Togo, their consequences on Burkina, frontier country, in a context of starting in this country of the structural adjustment programs (1991) and the unballastings in Senegal (Nubukpo, 2003). The grave crisis of treasury in Niger in 1992 and more recently, the policy unrest in Ivory Coast (2010-2011) are the other reasons for the introduction of dummies variables in our model.

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Economic Diversity and the Resource Curse: A Dynamic Panel Model

Economic Diversity and the Resource Curse: A Dynamic Panel Model

This result is important for the following reasons. First, we join other researchers who have established a positive direct relationship for the diversity-growth nexus (e.g. Hackbart and Anderson, 1975; Dissart, 2003; and Pede, 2013). Second, the GMM technique employed addresses the issue of endogeneity which is a major limitation that qualifies most results in this area. Finally, the use of dynamic panel techniques is a major advance because it helps to capture structural change and industrial transformation in regional economies. As pointed out earlier, Wagner and Pede express their concerns that diversity is a static measurement, while diversification and growth are dynamic concepts. They therefore conclude that it would be difficult for static measures to capture the changing structures of regional economies – the so- called diversification effects. Since we use a dynamic panel data model, our paper provides better insights on the static-dynamic nuances in the analysis of economic diversity, improving on the work of O’Donoghue (1999) and Pede.

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Taxes and Economic Growth in Developing Countries : A Dynamic Panel Approach

Taxes and Economic Growth in Developing Countries : A Dynamic Panel Approach

Skinner (1988) used data from African countries to conclude that income, corporate, and import taxation led to greater reductions in output growth than average export and sales taxation. Easterly and Robelo (1993) use growth model and sample includes 32 developing countries to experiment with a method of obtaining average marginal income tax rates that combines information on statutory rates with the amount of tax revenue collected and with data on income distribution. As they would expect, there is a positive correlation between their income weighted average marginal tax rates and the level of real per capita income. This simply reflects the fact that developed economies tend to rely more on income taxes than less developed countries. As for them, Padda and Akram (2009) tests whether tax policies conducted by Pakistan, India and Sri Lanka have transitory or permanent effect on their economic growth over the period 1973– 2008 and they find that the impact of tax rate changes is transitory and negative for short-term in Pakistan and India but for Sri Lanka its positive for first year and thereafter it has also negative effect on economic growth. By examining the impact of tax revenue on the economic growth of Nigeria judging from its impact on infrastructural development from 1980 to 2007, Worlu and Emeka (2012) find that tax revenue stimulates economic growth through infrastructural development. However, Bujang et al. (2013) investigates the long-run relationship between tax structure and economic growth and the other economic indicators via panel unit root tests and panel cointegration analysis in developing and high-income Organisation for Economic Co- operation and Development (OECD) countries. Panel cointegration test reveal that there is no long-run cointegrating relationship between tax structure and both of GDP and gross saving in developing countries. Moerover, Canavire-Bacarreza et al. (2013) evaluate the effect of the most important tax instruments of Latin American countries (personal income tax, corporate income tax, general taxes on goods and services, including value added and other sales taxes, and revenues from natural resource) on economic growth using vector autoregressive techniques, and for close to the entire region and a worldwide sample of developing and developed countries using panel data estimation. They find that, for the most part, personal income tax does not have the expected negative effect on economic growth in Latin America. They also find small negative effects of corporate income tax on growth for individual countries, specifically Argentina, Mexico, and Chile. Finally, their results suggest that greater reliance on consumption taxes has significant positive effects on growth in Latin American in general.

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Threshold Effects of Health on Economic Growth in Sub-Saharan African Countries: Evidence from a Dynamic Panel Threshold Model

Threshold Effects of Health on Economic Growth in Sub-Saharan African Countries: Evidence from a Dynamic Panel Threshold Model

Generally, studies which analyze the relationship between health and economic growth show a positive and significant relationship between them (Weil, 2007; Aghion et al., 2010; Sghari and Hammami, 2013; Vijesandran and Vinayag athasan, 2014; Atilgan et al., 2016; Wang and Liu, 2016 among others). However, the conclusions vary from one research to another. In fact, some studies stand out from the general trend, leading to a negative or insignificant effect of health on economic growth (Acemoglu and Johnson, 2007). In addition, most of the studies that have focused on the relationshipbetween the two variables assumes a linear relationship between them. This may be inconvenient because some studies show that macroeconomic relations are not always linear. More theoretical and empirical works have therefore started to examine the existence of non-linearity between economic growth and health. On the one hand, thisapproach aims to conciliate the divergent results obtained by the empirical studies. On the other hand, the hypothesis on which most of these works are based is that health is a variable that can contribute to enter (or leave) in a "poverty trap". Aisa and Pueyo (2006) showed that the impact of public health spending on economic growth is positive in poor countries and negative in developed countries. This implies that the impact of public health expenditure on economic growth depends on the level of development.

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Contribution of Advanced Technology and Foreign Capital to Growth of Different Stage of Development Countries

Contribution of Advanced Technology and Foreign Capital to Growth of Different Stage of Development Countries

Since all variables in the model are found to be non-stationary processes and be integrated of order one, the dynamic model is appropriate and the cointegrating relation of the production function was estimated. By using panel dynamic least square method, the long run cointegrating relations of the production function were estimated for the four groups of countries separately. This separated equation estimation can also help avoid the biased problem due to the possible omission of country specific factor as the separately estimated equations can be considered as each individual or independent function. This study showed that the pooled mean group panel dynamic model estimation for each group of countries provided better result than the panel fixed effect model. As a part of the superiority of the panel dynamic model estimated separately by each income group to be accounted for each country specific factor, the pooled mean group dynamic model allows short run dynamic to differ across countries while the aggregate panel fixed effect model does not have this dynamic effect.All the estimated production functions were found exhibiting non-constant returns to scale and were consistent with most findings of the new endogenous growth theory. Interestingly, all coefficients of factors were found significant for the OECD’s long run production function. At least one of those factors of growth was found insignificant for the other three lower income groups. The advanced technology and foreign capital can be the supporting factors and thus the OECD growth is better sustainable than the other countries. The finding indicates importance of advanced technology and foreign capital which are crucial factors apart from investment in human capital to sustain economic growth in the long run. All the five engines of growth were found being significant factors in the case of the successful OECD therefore a policy must be placed attention to these five factors to fully play their roles on growth.

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Binding constraints of economic growth on poverty: A dynamic panel data analysis

Binding constraints of economic growth on poverty: A dynamic panel data analysis

Empirically, significant number of studies, including Datt, and Ravallion (1992) tried to understand the growth-poverty nexus. They have done so by, among other things, closely investigating the role played by income distribution, as an important intermediate predicting factor of the poverty effect of growth in mean income. The existing literature on the role played by the income distribution is mixed. On the one hand, some results highlight the leading role of economic growth in reducing poverty, with zero effect of income distribution. The studies conducted by Ravallion and Chen (1997), and Dollar and Kraay (2002) are the most illustrative. One of the reasons advanced for the lack of income distribution effect on poverty is that the income of the poor increases equi-proportionately as those of wealthy. Romer, M. and Gugerty (1997)and Gallup et al., (1998) also demonstrate that, on average, the incomes of poor people tend to increase in the same proportion as the income of the rich people. On the other hand, other studies argue that income distribution is an important mediating factor in the effect of growth in mean income on poverty. Thorbecke (2013) notes that income inequality is one of the most important filters between growth and poverty. In this respect, evidence has been shown that the poverty effect of growth is high when inequality is low. For example, Fosu (2010) assesses the constraining effects of income inequality on Africa’s poverty reduction efforts. Using the so-called standard growth-poverty model, he finds that the poverty effect of a change in mean income is a decreasing function of inequality. He concludes that high inequality is extremely harmful to the speed at which growth is impacting poverty. Moreover, Ravallion (2005) argued that intuitively the higher the initial level of inequality in a country, the less the poor will benefit from growth, unless the growth is accompanied by significant distribution changes to lower inequality.

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Financial liberalization, Foreign Direct investment (FDI) and Economic Growth: A Panel Dynamic Data Validation

Financial liberalization, Foreign Direct investment (FDI) and Economic Growth: A Panel Dynamic Data Validation

The aim of this study is to show that financial liber alization, as a deter minant of financial development, can stimulate the r elationship betw een for eign dir ect investment (FDI) and economic gr ow th. Two distinct components have been analyzed. The fir st one is a theor etical component in w hich w e tr ied to tr eat the r elationship betw een financial development, inter nal financial liber alization, and FDI using an endogenous gr ow th model. The second component consists of an empir ical study w hich tr ied using a panel data to validate the previously stated theor etical r elationship. The sur vey, cover ing a sample of sixty nine developed and developing countr ies enabled us to r each thr ee fundamental r esults. Fir st, w hen financial syst ems ar e non-liber alized, w e have noted that FDIs had a negative effect on GDP gr ow th per capita. Second, w hen FDIs ar e implemented in countr ies char acter ized by their developed financial sector they gener ate positive effects on gr ow th. This implies that the key var iable w hich deter mines FDI efficiency is the degr ee of financial syst ems liber alization. Consequently, in non-liber alized financial systems FDIs effects on gr ow th ar e challenged. Thir d, w e show ed that financial development level is a str ategic var iable w hich positively affects gr ow th.

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Examining the impact of financial development on the environmental Kuznets curve hypothesis

Examining the impact of financial development on the environmental Kuznets curve hypothesis

This study aims to contribute to the financial development-economic growth nexus by building a simple model within a static and dynamic framework to investigate the validity of the Environmental Kuznets Curve (EKC) hypothesis. One of the main novelties of the paper is that it strongly accounts for the presence of cross section dependence along the suggested Pesaran (2004) CD tests. Moreover, it utilizes “second-generation” panel unit root tests in order to uncover possible cointegrated relationships an issue that has been overlooked by the existing empirical literature on EKC. The reason for using this kind of unit root testing can be justified by the fact that traditional stationarity tests (known as “first-generation” tests) suffer from size distortions and the ignorance of cross section dependence (Apergis, 2016).

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Financial Liberalization, Foreign Direct Investment and Economic Growth:  A Dynamic Panel Data Validation

Financial Liberalization, Foreign Direct Investment and Economic Growth: A Dynamic Panel Data Validation

ABSTRACT: The aim of this study is to show that financial liberalization, as a determinant of financial development, can stimulate the relationship between foreign direct investment (FDI) and economic growth. Two distinct components have been analyzed. The first one is a theoretical component in which we tried to treat the relationship between financial development, internal financial liberalization, and FDI using an endogenous growth model. The second component consists of an empirical study which tried using a panel data to validate the previously stated theoretical relationship. The survey, covering a sample of sixty nine developed and developing countries enabled us to reach three fundamental results. First, when financial systems are non-liberalized, we have noted that FDIs had a negative effect on GDP growth per capita. Second, when FDI are implemented in countries characterized by their developed financial sector they generate positive effects on growth. This implies that the key variable which determines FDI efficiency is the degree of financial systems liberalization. Consequently, in non- liberalized financial systems FDI effects on growth are challenged. Third, we showed that financial development level is a strategic variable which positively affects growth.

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Health, Education and Economic Growth: Evidence from Sub Saharan Africa (Dynamic panel analysis)

Health, Education and Economic Growth: Evidence from Sub Saharan Africa (Dynamic panel analysis)

The seminal papers on endogenous growth theory highlight the importance of human capital in the development and economic growth process. For instance, in their endogenous growth model, Lucas (1988) and Roomer (1990) take into account human capital through education stock for the former; with technology and research and development (RandD) for the later. In this study, health education proxy for human capital is considered as a positive externality on capital productivity and its accumulation favorably influences economic growth and welfare of a community.Alternatively, human capital is the stock of knowledge, competence, health, training, including creativity and other investments, embody the ability to perform labor tasks more productively.Besides, humancapital formation refers to the process of acquiring and increasing the number of people who have the skills, good health, education and experience that are critical for economicdevelopment. Although human capital is comprehensive, many theories explicitly connect investment in human capital development to education and occult the other aspects, mainly stock and investment in health. However, health also plays an important role in human capital accumulation and is closely connected to education. For instance, a healthy population is easy to educate and the efficiency of people to produce human capital is also high. Inversely, an increase in education involves the enhancement of health conditions as qualified people have a more responsible behavior.

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Threshold Effects of Inflation on Economic Growth: Evidence from Dynamic Panel Threshold Regression Analysis for 18 Developed Economies

Threshold Effects of Inflation on Economic Growth: Evidence from Dynamic Panel Threshold Regression Analysis for 18 Developed Economies

Inflation and growth nexus still a main focus in many studies as the existence of trade-off issue in inflation-growth relationship. The objective of this study is to estimate inflation threshold and its impact on inflation-growth relationship. This panel data study involves 18 developed countries over the period 1980–2016 with Consumer price index (CPI) and Gross domestic product (GDP) as variables associated with other determinants such as producer price, exchange rate, trade- openness, interest rate and population growth rate. Dynamic Panel Threshold Regression (DPTR) model that suggested by Kremer et al. (2013) is employed to estimate the threshold of inflation and its effects on economic growth. Our study extended the non-dynamic panel threshold model of Hansen (1999). Our results confirmed that the targeted inflation rate 2% by many central banks is a wise decision if compare to 4% as the impact of inflation on growth in lower inflation regimes is positive and statistically significant at the 5% level. For higher inflation regime, we estimate that inflation rates exceeding 1.44% are associated with lower economic growth, inflation and growth is negatively correlated and statistically significant at 1%. Trade-off relationship only exists at lower regime. By using GMM and Pooled OLS estimation, DPTR model results are proven robust where there is a U-shaped exist. Keywords: Inflation, growth, developed economies, dynamic threshold regression.

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Entrepreneurship, growth and unemployment: A panel VAR approach

Entrepreneurship, growth and unemployment: A panel VAR approach

Technological growth, entrepreneurship, and unemployment influence each other in numerous ways, forming a trio of inter-related components, yet the literature has traditionally emphasized the endogenous determination of one or two components of this trio. In this study we intend to elaborate on the interrelationship between entrepreneurship, unemployment and economic growth in a dynamic context using vector auto-regressions (VAR) with panel data across 30 OECD countries for a period covering 1970 to 2011. We use data from the Compendia dataset to estimate three empirical specifications for entrepreneurship, growth, and unemployment. On the right-hand side (RHS) of them there are lags of entrepreneurship, unemployment, and growth in our benchmark model, which we later enrich by including control variables according to the relevant literature. Each equation is estimated with Difference GMM and System GMM estimators. Moreover, an AR(2) model with additional control variables that include the degree of market capitalization and the equity level is estimated with system GMM. The results are enhanced by including macro-economic variables such as R&D spending, Taxes and Wage levels in our specifications. Finally, we use a Propensity Score Matching (PSM) estimator to overcome a selections bias in a country's decision to perform entrepreneurship targeting.

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Heterogeneity, trust, human capital and productivity growth: Decomposition analysis

Heterogeneity, trust, human capital and productivity growth: Decomposition analysis

In response to an upsurge in interest in ethnic heterogeneity, social capital, and general trust from a interdisciplinary point of view, increasing research has recently been devoted to accounting for how socio-economic factors affect economic growth. It thus seems to be open to question whether the influences of socio-economic factors on capital accumulation and diffusion of technology are different. There have been, however, few attempts to examine the channels through which socio-economic factors have an effect upon productivity growth. Accordingly, this paper, rather than putting an emphasis on just productivity growth, decomposes it into some components and then carefully investigates them. To this end, using panel data from Japan, which is characterized by a homogenous society, this paper employs the DEA method and a dynamic panel model.

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Financial Development and Economic Growth: Evidence from a Heterogeneous Panel of High Income Countries

Financial Development and Economic Growth: Evidence from a Heterogeneous Panel of High Income Countries

may lead to serious biases that cannot be remedied with instrumental variable estimation. The Mean Group Estimator of Pesaran and Smith (1995) is an unweighted average of the country specific coefficients and is particularly sensitive to outliers. A simple Random Coefficient (RC) estimator, on the other hand, calculates a variance weighted average, but it is not possible to estimate dynamic RC models. The Mixed Fixed Random (MFR) effects approach of Hsiao et al (1989) which has been utilized by Weinhold (1999), and Nair- Reichert and Weinhold (2001) falls somewhere in between the two extremes of FEE and MGE in terms of allowing for heterogeneity. This method imposes more structure on the coefficient values of the exogenous variables than the MGE. As compared to the FE estimator with a small T, the MFR coefficients approach produces a considerably less biased parameter estimate [Nair- Reichert and Weinhold (2001)]. Weinhold (1999) shows that the MFR coefficients model performs very well compared to instrumental variables (GMM), and it has other features well suited for the causality analysis in heterogeneous panel data sets.

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The effect of exports and imports on economic growth in the Arab countries: A panel data approach

The effect of exports and imports on economic growth in the Arab countries: A panel data approach

The exports and imports play important role on economic growth in the developed and developing countries. The economic growth is one of the most important determinants of economic welfare. The relationship between exports and topic of discussion, when economists try to explain the different levels of economic growth between countries. Exports of goods and services represent one of the most important sources of foreign exchange income that ease the pressure on the balance of ments and create employment opportunities. According to Feder (1982), exports contribute to economic growth in a greater capacity utilization, economies of scale, incentives for technological improvement and pressure n, leading to more efficient management. Thus, marginal factor productivities are expected to be higher export industries. The cross- sectional analysis by Feder (1982) and Ram (1987) confirm

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A Dynamic Model of Economic Growth in a Small Tourism Driven Economy

A Dynamic Model of Economic Growth in a Small Tourism Driven Economy

In this paper we studied the effects of an increase in foreign income growth, translating in an increase in the growth rate of tourism demand, on economic key variables of a small island economy that is completely specialized in the production tourism services by means of an AK technology. We found that an increase in the growth rate of foreign income initiates transitional dynamics, as the economy cannot (i) immediately move along its new balanced growth rate and (ii) be isolated from the rest of the world’s developments via proper price adjustments. The increase in foreign income growth, leading to a boom in tourism demand, is met by a higher rate of capital accumulation and thus tourism production and a gradually increasing price of tourism services (i. e., the terms of trade), to keep demand in line with supply. The increasing price of tourism services makes investments into tourism production more attractive, speeding thus up its growth rate. Hence, as time passes, the island economy experiences a phase of increasing growth. Eventually, it reaches its new balanced growth path, where prices remain constant and the economy’s growth rate is proportional to the growth rate in foreign.

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Large Agglomerations and Economic Growth in Urban India: An Application of Panel Data Model

Large Agglomerations and Economic Growth in Urban India: An Application of Panel Data Model

13 Regression (7) considers both the agglomeration variables together and shows the statistically insignificant non-linear effect of urban agglomeration on large city output growth rate. However, regression (8) and (9) show the statistically significant coefficient of the agglomeration variables in the non-linear form. The coefficients again have their expected sign and the results confirm the Williamson hypothesis. In the GMM- Differenced estimation of regression (8) the (log) income point that maximizes any positive effect of urban agglomeration on urban economic growth equals 10.52, which is the city output per capita at 1999-2000 constant prices of about Rs. 37049. The result indicates that increases in urban agglomeration are harmful, but just less so for a city output per capita of about Rs. 37049 at 1999-2000 constant prices. As expected the coefficient of the large city population agglomeration in regression (10) has a positive and statically significant effect on city output growth rate. In particular a 10 per cent increase in urban agglomeration increases urban economic growth by 23 per cent. Moreover, second proxy variable of urban agglomeration (i.e., large city population density) has a significant and positive effect. These results validate the hypothesis of positive effects of large urban agglomeration on urban economic growth. However, due to availability of limited number of observations for other explanatory variables we are unable to get satisfactory results (results are not reported here) by including them as explanatory variable in the GMM-Differenced regression estimation.

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Toward Understanding Outbound GCC International Tourism: The Role of Expatriates and Institutional Quality

Toward Understanding Outbound GCC International Tourism: The Role of Expatriates and Institutional Quality

Similarly, countries with a higher degree of tolerance toward the Muslim way of life, as captured by the civil liberty variable, tend to receive a fair share of the tourist flows from GCC. Columns 2 to 4 in Table 2 present the results corresponding to the joint estimation of all the variables above the baseline model. For the entire sample (Column 2) and high-income (Column 3) and low-income samples (Column 4), the Civil Liberty coefficient is positive and statistically significant, supporting our claim that civil liberty rights are crucial for GCC visitors in selecting tourism destinations.

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