ARDL Bounds Testing Approach

fertilizers and rice production in Pakistan. This study used Augmented Dickey Fuller (ADF) and Phillips Perron (PP) unit root tests to check the order of integration of each variable. The cointegration analysis with ARDL bounds testing approach is used to examine the impact of climate change on rice production in Pakistan over time series data from the period 1968 to 2014. The parameter stability test of the model is also checked at the end. The results of estimation show that the important variables of the study are cointegrated demonstrating the presence of long-run association among them. Furthermore, climate change factors, e.g. CO 2 and temperature have a

The study at hand investigated the determinants of inward FDI in Mongolia by analyzing the short- and long-run relationships among FDI, domestic market size, human capital, macroeconomic uncertainty, financial development, trade barriers, and infrastructure level. In doing so, the ADF and PP unit root tests, the most recently developed ARDL bounds testing approach to cointegration, FMOLS, and the Granger causality test within the VECM framework were employed. Ultimately, the results show significant short- and long-run relationships between FDI and its determinants. Domestic market size and human capital were found to exhibit a U-shaped relationship with FDI inflows, with an initial positive impact on FDI in the short-run, which then turn negative in the long-run. Macroeconomic instability was found to deter FDI inflows in the long-run. In terms of the impact of trade on FDI, imports were found to have a complementary relationship with FDI; while exports and FDI were found to be substitutes in the short-run. Financial development was also found to induce a deterring effect on FDI inflows in both the short- and long-run; thereby also revealing a substitutive relationship between the two. Infrastructure level was not found to be significant on any conventional level, in either the short- or long-run. In terms of Granger causality, bidirectional causality was found between FDI and GDP, EXR, IM, and LAB in both the short- and long-run; between FDI and FIN in the long-run; and between FDI and EX in the short-run. Furthermore, a unidirectional causality was found running from PC to FDI in the long-run; and from FIN to FDI in the short-run.

This paper examines the effect of inflation (INFR) and unemployment rate (UNR) on economic growth which is measured by Gross Domestic Product (RGDP) in percent on in Jordan for the period 1976-2016. To achieve this objective unit root, Augmented Dickey Fuller test was used. Subsequently, the Autoregressive distributed Lag ( ARDL) bounds testing approach and Error Correction Model (ECM-ARDL) model are applied to examine the both long-run and short-run causality issues between the variables under consideration. The empirical results of the study revealed, the results of the unit root test indicate that Real Gross Domestic Product growth (RGDPG), unemployment and inflation are tested at first difference then the problem of unit root has disappeared and hence they have become stationary at first difference. The bounds tests suggest that the variables of interest are bound together in the long-run when RGDPG is the dependent variable. Also, there is a long run relationship amongst the variables when INFR is the dependent variable. The results indicate also that there is no significant Granger causality from INFR to UNR and from RGDPG to UNR and from RGDPG to INFR and from INFR to RGDPG as well the short run. The results of this study can be used by all respected authorities in Jordan, especially authorities of economic and social institutions, so that they could attempt to reduce and control unemployment and inflation to achieve economic growth.

In addition to the ARDL procedure, we adopt a simulation process by running variance decompositions (VDC) and impulse response functions (IRF) for further inferences. VDC and IR serve as tools for evaluating the dynamic interactions and strength of causal relations among variables in the system (Duasa, 2007). Variance Decomposition (VDC), an out of sample causality test, partitions the variance of the forecast error of a certain variable into proportions attributable to innovations or shocks in each variable in the system including its own (Masih and Masih, 1995, 1996). This means VDC can provide relativity between the variables in the system. A variable that is optimally forecast from its own lagged values will have all its forecast error variance accounted for by its own disturbances (Sims, 1982). Since the frequency of data used in the sample are annual data, the time horizon selected in the VDC are 3, 5, and 10 years in order to determine the degree of exogeneity/endogeneity of the variables. Moreover, the IRF trace the directional responses of the variables to a one standard deviation shock of another variable. The IRF are normalized in such a way that zero represents the steady state value of the response variable (Masih and Masih, 1995, 1996). This means we can observe the persistence of capital flight and other variables to variation in other variables.

The situation in which the possibility of a different order of integration is present, it is possible to do ARDL modelling and to develop a VAR model based on Toda- Yamamoto procedure (Toda and Yamamoto, 1995). The main assumption of the ARDL model is that the variables are not integrated at I (2), as the calculation of the F statistics will be invalid in decision making on existing the long run relation. The ARDL testing approach can be implemented if variables have order of integration I (1), I (0) or are mutually integrated. Therefore, the previous procedure applied three different unit root tests. The results obtained show that the maximum order of integration is at I (1). The results of Zivot and Andrews unit root test are shown in the table 2. In this way the robustness of stationarity properties is proved, which is further studied through this kind of a unit root test. Previous unit root tests is a necessity that must be implemented to avoid the possibility of certain variables being of the order I (2) or higher.

This study considered a bivariate analysis between the impact of real gross national product per capita as measure of economic conditions on fifteen categories of crime, in Malaysia namely; total crime, violent, murder, attempted murder, armed robbery, robbery, rape, assault, property, daylight burglary, night burglary, lorry-van theft, car theft, motorcycle theft and larceny. In this study we employed the autoregressive distributed lag (ARDL) bounds testing procedure to investigate the long-run relationship between economic conditions variable and criminal activity using annual data for the period 1973 to 2003.

The results of the short-run relationship estimated by ARDL model depicts that there are the significant negative relationship of D (ln INF) and D (ln RER) with D (ln EX). The negative relationship between RER and EX indicates the real exchange rate reduced the export performance of a country. It is on the par with the existing literatures that exchange rate has negative impact on the export of a country which already proved by the study of Doroodian (1999), Arize (2000), Sauer & Bohara (2001); and Doganlar (2002). The results still confirm that there is positive and statistically significant relationship in the short run among D (ln TL) and dummy variable of Crisis with EX. Therefore, the insignificant relationship between ODA and EX could be explained the effectiveness of official development assistant which is subjective to several factors might not be effective in the short run. As World Bank (2005) specified the factors such as investment and improvement in the trade facilitating infrastructure—roads and ports—have influences or offset on the relationship among these two variables. Also, others studies investigate the role of geographical characteristic of economy (Collier, 2008) and degree to vulnerability to external shocks—price shocks or extreme events (Collier & Dehn, 2001; Guillaumont & Chauvet 2001;2002) has been supported that the effectiveness of ODA on export performance depends on other factors. In addition, the 10% significant level and negative sign coefficient of ECM (t-1) for the selected models indicates the relative speed of adjustment exist to bring the long run equilibrium in the selected model which confirms that the model is corrected from the short run toward the long run equilibrium at adjustment rate of 92%.

Explaining the sources of economic growth has ranked amongst the most significant issues that economists have examined. Romer's 1986 work began a set of theoretical and empirical analyses focusing on the endogeneity of the growth process as compared to Solow (1956) type neoclassical growth models which use an aggregate production function approach and exogenous technical changes. Information and Communication Technology (ICT) has become, within a very short time, one of the basic building blocks of modern society. Many countries now regard understanding ICT and mastering the basic skills and concepts of ICT as part of the core of economic growth process. Within the past decade, the new ICT tools have fundamentally produced significant transformations in industry, agriculture, medicine, business, engineering and other production fields; moreover ICT has an added value to the final goods and services. The widespread diffusion of the Internet, mobile telephony and broadband networks all demonstrate how pervasive this technology has become. But how precisely does ICT affect economic growth? And what are the conditions under which ICT can become effectively enhance the economic performance?

Macro-analysis suggests that the nominal exchange rate needs to be adjusted for variations in local and international prices. After adjustment, nominal devaluation policy would be effective and improve the trade balance, if nominal devaluation leads to real devaluation. Bahamani and Kara (2003) investigated the import and export demand functions for nine industrialized countries like Australia, USA, and Canada etc. The data were used on a quarterly basis for the period 1973-98. For economic analysis they used ARDL bounds testing approach. Their results highlighted that long run income elasticities were greater in import demand function than in the export demand function. The price elasticities were smaller than unity, indicating that import and export demand functions were relatively inelastic. They failed to provide any specific answer to the policy question that which policy has quickest impact on trade. They found trade flows of different countries do react differently. Santos- Paulino and Thirlwall (2004) investigated the impact of trade liberalization on imports, exports and the balance of trade for 22 developing countries. They tested the impact and significance of liberalization using different estimation techniques such as the fixed effects and generalized method of moments (GMM) for panel data analysis. They found that the impact of trade liberalization on import growth was greater than on export growth for developing countries. Hussain (2004) estimated total and disaggregated import demand functions for Bangladesh during the period 1973-2000. Ordinary Least Squares (OLS) method was used for linear and log- linear import demand equations. He found income elasticity positive as expected for all commodities, except rice and wheat. The coefficients of relative prices ranged from -1.66 to -0.73 for all the commodities, but the coefficients of relative price for rice and soya bean oil were found to be negative even though they were not statistically significant.

15 electricity consumption, trade openness, economic growth, capital and labour. The method has several advantages over the traditional ones. For example, the method applies even if the regressors are integrated at I(1) or I(0) or I(1)/I(0). A dynamic unrestricted error correction model can be derived from the ARDL bounds testing through a simple linear transformation. The ARDL bounds testing approach is better suited for small sample as in this paper. An unrestricted error correction model (UECM) combines the short-run dynamics with the long-run equilibrium without losing any long-run information. The UECM is expressed as follows:

This study investigates the inter-temporal causal relationship between energy consumption and economic growth in Bangladesh during the period 1971-2007. This issue is of fundamental importance for the developing economy of Bangladesh. We use the Autoregressive Distributive Lag (ARDL) bounds testing approach to cointegration tests to explore the dynamic relationship between energy consumption and economic growth in Bangladesh. We apply newly developed methods based on simulations that are robust to the violation of statistical assumptions especially when the sample size is small as is the case in this paper. The interesting results of the paper are that unidirectional causality runs from energy consumption to economic growth in Bangladesh and then restrictions on the use of energy could lead to a reduction in economic growth. There is a convergence process in the long-run dynamics of energy use to real GDP so that any shock in energy adjusts with real GDP by 2-2.5 year. The growth hypothesis suggests that energy consumption plays an important role in economic growth in Bangladesh.

Before proceeding to ARDL bounds testing approach to investigate long run cointegration between inflation, terrorism and economic growth, it is necessary to find out integrating order of the series. ARDL cointegration approach can be applicable if variables are integrated at I(0) or I(1) or I(0) / I(1) i.e. mixed order of integration. The main assumption of ARDL bounds testing approach to cointegration is that variables must be stationary at level or at 1 st difference if any variable in integrated at I(2) then computation of F-statistic becomes invalid to take decision about the existence of long run relationship. In doing so, we have applied three unit root tests i.e. ADF by Dickey and Fuller (1979), DF-GLS by Elliot et al. (1996) and Ng-Perron by Ng and Perron (2001) to ensure that no variable is integrated at I(2) 3 . The results indicate that series have unit root problem at level and found to be integrated at I(1). Baum (2004) argued that ADF, DF-GLS and Ng-Perron unit root tests provide biased results. The main reason is that these unit root tests do not have information about structural breaks occurring in the series.

Ng- Perron unit root test is applied to find the order of integration of the variables 2 . Our empirical analysis shows that all series are non-stationary at level but found to be stationary at first differenced form. We can conclude on the basis of our results that financial development, corruption and economic growth are integrated of order one. In the next step we apply ARDL bounds testing approach to cointegration in order to test the long run relationship between financial development, corruption and economic growth. But it is necessary to choose an appropriate lag order before applying ARDL approach to cointegration. The AIC criterion is used to choose appropriate lag length and to capture the dynamic relationship to choose a best ARDL model. Our selected lag order is 2 3 . The result of the ARDL approach is reported in Table-1.

The article empirically investigated economic growth as a function of foreign direct investment and exports in South Africa. The article applied the autoregressive distributed lag model, known as the ARDL bounds testing approach to cointegration for the long run relationship between economic growth, foreign direct investment and exports. The error correction model was used to examine the short run dynamics; and the VECM Granger causality approach was used to investigate the direction of causality. The article confirmed cointegration between economic growth, foreign direct investment and exports. The article indicates that both foreign direct investment and exports spur economic growth. The VECM Granger causality analysis found unidirectional causality between economic growth and foreign direct investment running from foreign direct investment to economic growth, unidirectional causality between foreign direct investment and exports running from foreign direct investment to exports and bidirectional causality between economic growth and exports. The article confirms the FDI-led growth hypothesis for South Africa. On the policy front, the government should stimulate foreign direct investment through incentives to investors, creation of a good macroeconomic environment and a careful utilisation of loose monetary policy to grow the economy.

This study employs the ARDL bounds testing approach to investigate causality implications between credit growth and current account deficits in the Turkish economy. This approach involves an error-correction framework which incorporates the short- and long-run information in the data as being a cointegration technique. On the other hand, it has certain advantages in comparison with the conventional cointegration techniques. First of all, the ARDL methodology avoids classification of the variables into I(1) or I(0) and does not require the variables to have the same order of integration. As pointed by Pesaran and Shin [11] and Pesaran et al. [12], the ARDL bounds testing approach can be implemented irrespective of whether the variables are purely I(0), purely I(1), or mutually cointegrated. The error-correction model, which integrates short-run dynamics to the long-run equilibrium, can be derived through a simple linear transformation of the underlying ARDL model. The long- and short-run parameters of the model in question are estimated simultaneously. The ARDL model takes sufficient numbers of lags to capture the data generating process and uses a dynamic framework of a general-to-specific modelling [49]. Finally, the small sample properties of the ARDL approach are superior to standard cointegration techniques [11,49].

The decision about cointegration in ARDL bounds testing approach depends upon the generated critical bounds by Pesaran et al. (2001). The null hypothesis of no cointegration is H : α INQ = α FD = α GDPC = α CPI = α TR = 0 the alternative hypothesis of cointegration is H a : α GDPC ≠ α CO ≠ α K ≠ α EMP ≠ 0 . Then next step is to compare the calculated F-statistics with lower critical bound (LCB) and upper critical bound (UCB) tabulated by Pesaran et al. (2001). The null hypothesis of no cointegration may be rejected if calculated value of F-statistics is more than upper critical bound. The decision may be about no cointegration if lower critical bound is more than computed F-statistics. Finally, if calculated F-statistics is between UCB and LCB then decision about cointegration is inconclusive. To check the reliability of the results reported by ARDL model, we have conducted the diagnostic and stability tests. In the diagnostic tests, we examine for the presence of serial correlation, incorrect functional form, non-normality and heteroscedisticity associated with the model. The stability test is conducted by employing the cumulative sum of recursive residuals (CUSUM) and the cumulative sum of squares of recursive residuals (CUSUM SQ ).

The results are reported in Table-3. The results indicate that variables do have unit root problem at level with a structural break both in intercept and trend. The both variables are found to be stationary at 1 st difference. This implies that the variables are integrated at I(1). The unique integrating properties of the both series leads us to implement the ARDL bounds testing approach to cointegration examining the long run relationship between financial development, economic growth and poverty reduction over the study period of 1975Q1-2011Q4 in case of Egypt. An appropriate lag order of the variables is needed to apply the ARDL bounds testing. Various lag length criterion are available indicated in Table-4. We followed Akaike information criteria to select appropriate lag length. It is pointed by Lütkepohl, (2006) that AIC has superior power properties for small sample data compared to any lag length criterion. Our decision about lag length is based on the minimum value of AIC. The results are reported in Table-4. It is found that we cannot take lag more than 6 in such sample data.

I(1). The unique integrating properties of the both series lead us to implement the ARDL bounds testing approach to cointegration examining the long run relation between economic growth, electricity consumption, trade openness, capital and labor over the study period in case of Kazakhstan. An appropriate lag order of the variables is needed to apply the ARDL bounds testing. Various lag length criterion is available indicated in Table 4. We followed Akaike information criterion to select appropriate lag length. It is pointed by Lütkepohl, (2005) that AIC has superior power properties for small sample data compared to any lag length criterion. Our decision about lag length is based on the minimum value of AIC. The results are reported in Table 4. It is found that we cannot take lag more than 1 in such small sample data.

While the root causes of terrorism are multidimensional – ranging from religious extremism to a sense of alienation from society to anger at perceived geopolitical injustice – economic factors can help explain the rise of terrorism. With the help of the ARDL bounds testing approach followed by variance decomposition (VDC) and impulse response (IR) function, this study provides an empirical investigation to determine the causal relationship of the variables of economic growth, trade, military spending, education spending and unemployment on the onslaught of terrorism in Pakistan. The results of the overall study clearly conform to the deprivation and modernization hypotheses that underdevelopment and poverty do provide fertile grounds to terrorists for new recruits while unequal growth could equally facilitate the spread of terrorism. According to our analysis, in the short run, terrorism is most affected by the variables of trade and GDP. However, in the long-run, two startling outcomes are the positive and significant relationships between GDP growth and terrorism, and also between military spending and terrorism which imply that increased economic growth and military spending breed terrorism. The first relationship can be explained on the basis of rising income inequality and modernization hypothesis. The second linkage can be the aftermath of government’s asymmetric military spending at the expense of critical development sectors like education which significantly reduce the opportunity cost of terrorism in the society as elicited by a significant long-run relationship between military spending and education. The overall result of the study has many significant policy implications including shifting the precedence of military spending and war on terror towards the more desirable socio-economic sectors of education, trade and employment.

This study used the Autoregressive Distributed Lag (ARDL) Bounds testing approach and Toda- Yamamoto Non-granger causality test to analyze respectively the long-run and causal relation- ships among economy performance, foreign direct investment, domestic investment and port sec- tor production output in Cote d’Ivoire over the period 1980-2013. The empirical results illustrate that economy performance, foreign direct investment and domestic investment are significant in explaining the productivity of port sector. Therefore, the study suggests focusing on investment strategies that involve private (foreign and domestic) participation in projects dedicated to im- prove the safety, quality of operations in the sector and transport connectivity.