ardl test in stata forex
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Ardl test in stata forex does steam accept cryptocurrency

Ardl test in stata forex

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We use demo license of Stata In this paper, we used two variables natural logarithm of per capita gross domestic product GDP and natural logarithm of per capita international and national tourism expenditure ITE to study the relationship between the tourism sector and economic growth in Algeria over the period of — We established with the unit root test with and without breakpoint that the variables are stationary in the first difference and there is a structural break in ITE and GDP.

Thus, with the presence of a breakpoint, we employed the methodology of Gregory—Hansen to avoid such issue, but we found that there was no evidence of cointegration with breakpoint, so then we used the vector autoregressive model VAR. The model showed that the tourism sector has a positive and insignificant coefficient on the economic growth, while the economic growth factor has a positive and significant on the tourism sector. Keywords: Tourism, Economic growth, Unit root test with and without breakpoint, Cointegration with breakpoint, Breitung and Candelon causality Introduction The economic growth has been linked with different sectors such as basic agricultural, tourism and industrial sectors as well as the flow of foreign capital.

But, nowadays, many nations should diversify their economic situation and they ought to give more importance to the tourism sector. In , Papatheodorou [ 41 ] concluded from his analysis in the Mediterranean region that the role of tourism in economic growth has been underestimated as a sector without a clear growth trend. Since then, the tourism sector has started to take a major place in society and it has drawn attention to its ability to expand and diversify into becoming one of the fastest growing economic sectors in the world.

Tourism is growing continuously despite repeated infrequent crises due to terrorism, natural disasters and COVID pandemic. Also, it plays a strategic role in the government development and it represents a vital element in achieving sustainability and increases the investment possibilities.

According to the World Tourism Organization, the number of international tourist arrivals 1 expanded at an annual rate of 6. According to World Bank Statistics [ 24 ], 2 it shows that the number of international tourist arrivals rose from million in to more than 1 billion and million in Besides, it becomes a competitive global industry for its effective strategic role in the development of nations, where a group of researchers has concluded that there is a single trend of economic growth to the tourism sector [ 2 ].

Also, there are some scholars who found that the tourism sector impact and cause positively the economic growth [ 8 , 9 , 20 , 42 , 48 , 53 ]. Moreover, the investment in the industry sector is a vital element in achieving sustainability for any country, and any rise in the capital flows will affect the size and the distribution of different tourism projects and the flow of their aggregates to the regions of increasing their revenues and profits [ 21 ]. Therefore, the development of the tourism services will be beneficial for any country, where some of them have a modest natural resources and wealth.

Thus, with good tourist assets, any country will be able to build a strong economy based on the tourism sector [ 11 , 19 ], but setting up a country for tourism is difficult due to the cost of the infrastructures.

Algeria, like other countries, seeks to achieve a comprehensive development that reaches the socioeconomic growth and stability, but its economic situation depends mainly on the oil sector. To finance and to diversify the process of the economic development, Algeria should focus on the tourism sector due to the possibilities that can offer.

Hence, an adoption of a huge tourism program and strategic investment will generate a high profit, which they will be aimed at promoting and supporting the industrial economy without depending a lot on the oil sector. However, the reality has proved that the measures taken and the limited sector are not effective in contributing to the economic growth and therefore did not rise to an alternative developmental level due to the obstacles that prevented it, such as the Arab Spring, an unprecedented wave of political violence and terrorist acts which have happened in several MENA tourism-dependent economies, keeping tourists away from Egypt, Tunisia and Turkey, and also now the health issue with COVID pandemic which has cut every economic activities around the world.

The goal of this study is to investigate the relationship between the tourism sector and economic growth in Algeria during the period of — This paper demonstrates the importance and the role that can play the tourism sector in the Algerian economic growth by using an econometric model. Literature review A large literature has examined the connection amongst tourism and economic growth for several nations, often showing the relationship to vary depending on the specific country investigated, the time periods considered and the methods employed.

One strand of literature argues for tourism-led economic growth TLEG hypothesis that views tourism as a strategic factor for long-term domestic economic growth, generating direct, indirect, or induced effects on other productive sectors [ 57 ]. Balaguer and Cantavella-Jorda [ 3 ] found a one-way causality from tourism to economic growth in Spain. Brida et al. Dritsakis [ 17 ] confirmed the beneficial effect of tourism on GDP in seven Mediterranean countries.

Related results are established in Lanza et al. In fact, of the 87 empirical analyses studied, Pablo-Romero and Molina [ 40 ] described that 55 investigations showed evidence in support of the TLEG hypothesis. Contrary to the TLEG hypothesis, the second stream of literature declares that economic variations are the driving force behind the tourism sector, which is often referred to as the economic-driven tourism growth EDTG hypothesis.

The reasoning underpinning the EDTG assertion is that resource availability, infrastructure development and political stability creates an ambient economic climate that promotes tourism activities. Oh [ 38 ] established that the economic growth Granger-causes tourism in South Korea, but not vice versa in the short run.

The studies of [ 32 , 37 , 43 ] confirmed an evidence of the EDTG hypothesis in various other countries. Cecchetti et al. Several studies argue that there is a non-linear link in which increased government debt may increase economic growth initially but after a certain point lead to a decrease in the growth rate. Based on historical data series for two decades, they analyse the link among inflation, high central sovereign debt, and economic growth in both developed and developing nations.

However, the Rogoff and Reinhart results have become controversial due to some computational errors in their calculations that were pointed out by Herndon et al. Kumar and Woo find a similar result using panel data for 38 advanced and emerging countries.

However, the quadratic relationship is very sensitive to extreme values, particularly in a small sample of observations as pointed out by Panizza and Presbitero Presbitero uses total government debt in analysing the debt-growth link in developing countries for the period — Apart from the non-linearity debate, the issue of reverse causality needs to be taken into consideration, that is, whether debt leads to higher growth or vice-versa.

Their results suggest that the two-step GMM is more favourable regarding efficiency. Kumar and Woo use a system GMM dynamic panel regression approach to address the endogeneity issue. The GMM method is considered to be more efficient and give more precise estimations since this approach is applicable for large cross-country analysis see Roodman Presbitero also consider the foreign currency debt as a proportion of government debt, as an instrumental variable.

However, the use of this variable is questionable, in terms of the economic interpretation and according to Woo and Kumar this variable cannot meet the restriction criteria of a good IV estimator and its usage as an instrument is highly questionable for high-income countries where there is a low level of foreign currency proportion of debt. To avoid reverse causality, Woo and Kumar use initial debt levels to analyse the effect on future growth.

Due to the problem of finding suitable external instrumental variables, the standard system GMM estimator is used to address the potential endogeneity issue. They find that a high initial level of public debt is significantly associated with slower subsequent growth in a large panel of countries made up of developed and emerging market economies.

While Baum et al. They use the dynamic panel method of GMM to estimate the linear model and modified Caner and Hansen approach to estimate the debt threshold. Sen et al. In the spirit of debt overhang, they examine external debt and find that borrowing severely hinders growth in Latin America and has a mildly negative effect in the case of Asia.

However, the GMM only captures the dynamics of short-run and ignores the long-run relationship since the estimator is designed for a small time span. Consequently, as shown by Christopoulos and Tsionas the outcomes may show a spurious result instead of long-run equilibrium. Moreover, in the case of a small N and large T, the GMM estimator may suffer from an autocorrelation problem in the residuals of the first-difference estimation, see Roodman Focusing on time series estimation, the authors find that the adverse impact is persistent in the long-run, but there are positive effects for some member countries in the short-run.

Conversely, Eberhardt and Presbitero use a dynamic model of common correlated effects of pooled group and mean group estimators to analyse the link between debt and growth and they also use the traditional mean group and dynamic two-way fixed effects as a means of comparison. Using data from countries, the authors allow for heterogeneity in the long-run and short-run link. They find a significant positive effect on average in the long-run debt but an insignificant result in the short-run.

The use of panel autoregressive distributed lag ARDL models for analysing the impact of public debt on economic growth can also be found in Chudik et al. They also find no simple debt threshold for either developed or developing countries after accounting for the impact of global factors and spillover effects. The data set Panel estimation is chosen in this study to control for individual heterogeneity, to identify unobservable characteristics and to give more information on reliable estimation, see Baltagi Our analysis uses the data of 14 countries in Asia over a period of 33 years — , resulting in a total of observations see Table 1 for countries in the sample.

The choice of the countries was determined by issues of data availability. Japan was excluded from the analysis due its high public debt level. Table 1 provides comparative data for countries debt-to-GDP ratio. However, when T is larger than N as in our case the ARDL approach is appropriate and therefore is the preferred method for our analysis.

Following Ala-i-martin et al. With the inclusion of several control variables to overcome the problem of omitted variables bias. Trade openness in log : This study uses sum of import and exports as a percentage of GDP to account for international trade activity.

Methodology We use several econometrics methods to examine the relationship between public debt and economic growth particularly in Asian countries and consider both the long-run and short-run relationships, along with the presence of nonlinearity.

Preliminary tests We first conduct panel unit root tests before performing the main estimations, the tests are necessary to check whether the variables are non-stationary.

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Although ARDL cointegration technique does not require pre-testing for unit roots, to avoid ARDL model crash in the presence of integrated stochastic trend of I(2), we are of the view the unit root test should be carried out to know the number of unit roots in the series under consideration. This is presented in the next section. Mar 27,  · To further simplify, lets consider j=k=1, so that the ARDL (1,1) model for the relationship of consumption and income can be written as Model 1: Ct=a+b 1 C t-1 +d 0 Y t +d 1 Y t-1 +e t HereC denotes consumption and Y denotes income, a,b 1,d 0,d 1 denote the regression coefficient and e t denotes error term. 7/5/ · 1. Negative values have no issues but when you will transform into log it become unidentified or zero. So it will create problem as missing values. 2. Estimated Reading Time: 6 mins.