Before estimating the **model**, first perform data analysis such as testing unit root tests Augmented Dickey Fuller (ADF), test the degree of integration, the determination of lag length optimal, using the Akaike Information Criterion (AIC), Schwarz Information Criterion (SIC), and likelihood Ratio (LR), Engle Granger cointegration test.(Gujarati) Further done the testing of the econometric assumptions such as k normality, multicollinearity and autocorrelation.[16] This study uses Eviews 9 software to analyse the data. To know the specifications of the **model** with **error** **correction** **model** (ECM) are a valid **model**, can be seen in the results of statistical test to the coefficient of **error** **correction** term (ECT).[16] If the ECT coefficient is negative and significant, then the observed **model** specification is valid. If ECT is not significant, mean coefficient of ECT is equal to zero, then the estimation results above equation is known only to the coefficient of the short-term, while the coefficient of the long term of the independent variables used is not known when the purpose of econometrics is to return to economic theory related (long- term).[16] That is to say if ECT is equal to zero, the purpose of empirical studies fail.[16]

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Abstract— This study aims to examine the impact of trade liberalization i n South East Asia on Indonesia's food security and to analyze the factor that determines food security in Indonesia. **Error** **Correction** **Model** (ECM) approach was used to analyze time-series data from 1980 to 2016. The result is trade liberalization that mark e d by the implementation of the AEC (ASEAN Economic Community), trade barriers elimination among ASEAN member countries, and trade openness affected food security in Indonesia in the short -run and long run. In the short run, food security was significantly influenced by rice availability, consumption growth, openness, rainfall, and AEC implementation. While, rice availability, rainfall, and AEC implementation was influenced by food security in Indonesia in the long run.

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It would be interesting to see if the presence of drivers of electricity consumption other than GDP, as in ECM1, improves the forecasting ability of the **error** **correction** **model**. So we construct another ECM, denoted as ECM2, with real GDP as the only explanatory variable. We also present the forecasting performance of an elasticity-based **model** (where elasticity is the elasticity of electricity consumption with respect to real GDP). This is a commonly used forecasting method in the absence of an econometrically developed **model** because it is simple, can be done quickly, and does not require a sophisticated forecaster to implement. These models are presented below.

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Trade balance is one core component of national income of countries especially in the present times on which every nation have open economy and foreign interaction. It may be in positive or negative depending on the trading and economic power of the nation. For instance Ethiopia has a negative trade balance for the previous two decades, implies that export of the country could not cover the import expenditure. This indicates that the proportion between export and import is always less than one. There are different factors which result into having as such circumstance. This study tried to assess the main determinants of the trade balance of Ethiopia by considering ratio of export and import as an approximation to trade balance. The study implements **error** **correction** **model** to analyze a time series data from 1981-2011, collected from World Bank. The long-run co-integration result shows that GNI per capita, domestic inflation and trade dependency of the country have negative and significant integration with the ratio of export to import. Given this, world oil price inflation has positive and significant effect on the ratio. The vector **error** **correction** **model** of the short-run regression shows that the previous year ratio (Export/Import), elasticity to import, previous year world oil price, agricultural growth and previous year GNI per capita have positive and significant effect on the speed of adjustment of the long-run trend of the ratio. Given this, elasticity of export, previous year inflation and current year GNI per capita affects the speed of adjustment negatively and significantly. The ECM result shows that the speed of adjustment of the deviation from the long-run trend line is 91%, which indicates that Ethiopian economic system is responsive for each policy measures.

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This paper attempts to examine the short-run and long-run causal relationship between Kuala Lumpur Composite Index (KLCI) and selected macroeconomic variables namely inflation, money supply and nominal effective exchange rate during the pre and post crisis period from 1987 until 1995 and from 1999 until 2007 by using monthly data. The methodology used in this study is time series econometric techniques i.e. the unit root test, cointegration test, **error** **correction** **model** (ECM), variance decomposition and impulse response function. The findings show that there is cointegration between stock prices and macroeconomic variables. The results suggest that inflation, money supply and exchange rate seem to significantly affect the KLCI. These variables considered to be emphasized as the policy instruments by the government in order to stabilize stock prices.

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This article is designed to investigate the existence of relationship between daily per capita demand for nutrients (calorie, protein, and animal fat intake) and economic growth indicator measured by per capita real Gross Domestic Products (GDP). Using annual time series data covering 1961-2007 from Nigeria, the study employed vector **error** **correction** **model** (VECM). The daily per capita demands for nutrients are analyzed as endogenous variables while real per capita GDP was taken as exogenous variable. These series are defined in logarithm. Preliminary investigation revealed that the series were found to be I (1) process at initial level while the series become I (0) after first differences. The trace statistics test shows that the pear of the series on the daily per capita demand for nutrients and per capita real GDP are co-integrated. Hence, the results of VECM shows that in the long-run, per capita real GDP positively and significantly impact per capita demand for nutrients in Nigeria over the years. Specifically, we observed that 1% increase in real GDP significantly increases the demand for calorie, protein and animal fat by 0.073%, 0.068%, and 0.059%, respectively. Also, the result of the short-run dynamics indicated that the speed of adjustment of the demand for calorie, protein and animal fat intake towards long-run equilibrium relationship associated with the shocks in the real GDP from the previous period is about 29%, 41% and 26%, respectively in the current period. Furthermore, we noted that the result of the impulse response function lend support to the observation that real per capita GDP increases the demand for calorie, protein, and fat intake in Nigeria. Our findings provide no support for the hypothesis that growth in real GDP is constrained by the nutrient intake in the same period.

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This paper investigates the existence of long-run relationship between exports and imports in Qatar’s economy using Johansen cointegration approach. Qatar is a small open economy that depends on the outside world for exporting its oil, natural gas and its hydrocarbons and to import consumer and capital goods. Exports compose a major proportion of GDP. Annual data for the period from 1980-2011 were used. ADF and Phillip-Perron unit root tests were applied to time series data and variables were found to be integrated of order one. Exports and imports were found to be cointegrated and hence, a long-run relationship exists between exports and imports, and Qatar is not in violation of its international budget constraints. An **error** **correction** **model** was specified and imports were found to Granger cause exports in the long-run.

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There are several mechanisms that can account for short-run business cycle transmission. International trade is probably the major vehicle, and it forms a direct channel through which income and price shocks may be transmitted. Capital flows provide a second mechanism which is most likely to be responsible for the transmission of interest rate, monetary and exchange rate shocks (Selover, 1997). There is already a substantial theoretical literature on international business cycle transmission and many models of how an income shock may be transmitted from one country to another. Based on the above explanation, this study has attempted to analyze the business cycle transmission between the USA and Indonesia by focusing on the transmission of industrial production, prices and interest rate shocks. The issue has been inspired by the saying that if the USA sneezes, the ASEAN Countries catches a cold in almost all ASEAN countries. The saying implies that the U.S. economy drives the ASEAN Countries economy. The present study has attempted to examine the proposition focusing on Indonesian by testing co-integration and estimating a vector **error** **correction** **model**.

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This research analyzes the short- and long-term influence of rice prices on the welfare of Indonesian farmers using an **error** **correction** **model**. Drawing upon data from Indonesia's Central Bureau of Statistics, it reveals that rice prices exert significant positive short-run effects and no significant long-run influence on farmers' welfare. These findings extend or refine results from earlier studies that lack the time series perspective of our research. They also support policy intervention by the Indonesian government to increase farmers' welfare and assure food supply.

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The aim of this paper is to study financial integration between emerging MENA countries and developed countries. We study short-term price series dynamics using Johansen’s (1991) multivariate cointegration test to determine the number of cointegration vectors and Granger’s (1987) causality test to determine causality direction across markets. The vector **error** **correction** **model** (VECM) **model** combines long-term cointegration modeling with short-term dynamics to determine equilibrium return rate. The results point to the presence of two long-term cointegration vectors between MENA and developed countries, while causality direction is bidirectional. The VECM results suggest the presence of a short-term cointegration between these countries. VECM’s residuals and the Wald test confirm the robustness of our **model**.

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Studying exchange rate requires appropriate approach in order to tackle all aspects that encompass it. Hence the dynamic analysis facilitates the managing of exchange rate moreover it explains factors that effect it. Dynamic econometrics provides smooth technique for dealing with relation overlapping long run equilibrium as well as short run. We resort to dynamic econometrics because classical one is unable to hold the at convey long run equilibrium on the steady state rate of the phenomena under study. The classical regression the none stationary properties of the variables were not hold exactly. Accordingly the results draw on will not help in drawing precise interpretation and consequently future forecast. Based on above justification we need to realize and test the stationary nature if the suggested **model** variables more over to inquire uilibrium relationship or not and consequently estimating the such relation via namely, **error** **correction** **model** such technique can be justifiable when all variables or some of them were not stationary beside exiting long run equilibrium

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To examine the relationship between investment in human capital and economic growth in the Kingdom of Saudi Arabia for the period 1970-2014. Quantitative research design has been implemented. Granger Causality approach has been employed, followed by **error** **correction** **model**. The data stationarity and integration order have been tested, using the augmented Dickey-Fuller. Any long-run or short-run causality was not observed between expenditure on education and economic growth (per capita gross domestic product). 73.6% variation has been indicated by fixed capital formation of gross national product, which is considered as an effective aspect. The results indicated that results are statistically significant with P value (0.000) at 5% level of significance. Investment in human capital, with the right policy assessments and rehabilitation, can be translated into an essential element of growth in the Saudi economy.

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The focus of this paper is on testing for a single cointegrating vector. In section II we derive critical values for an alternative test based on the joint significance of the levels terms in an **error** **correction** **model**. We demonstrate that these critical values differ from those derived from the standard F-distribution in that they are consistently larger. In section III we compare the performance of our test statistic with the Engle-Granger test and the Kremers et al test. We show that our test has more power in rejecting a false null hypothesis when compared with the Engle-Granger test. We also show that our testing procedure has an advantage over the Kremers et al test in that it generates critical values which are not sensitive to the parameters of the particular **error** **correction** **model** we estimate. Section IV presents an example using monthly data for UK and US interest rates and Section V gives our conclusions.

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The concept of cointegration ( Granger (1981), Granger and Weiss (1983), Engle and Granger (1987)) has been successfully applied to modelling multivariate nonstationary time sereis. The lit- erature on cointegration is extensive. The most frequently used representations for a cointegrated system are the **error** **correction** **model** (ECM) of Engle and Granger (1987), the common trends form of Stock and Watson (1988), and the triangular **model** of Phillips (1991). The **error** correc- tion **model** has been applied in various practical problems, such as determining exchange rates, capturing the relationship between expenditure and income, modelling and forecasting inflation, etc. From the equilibrium point of view, the term “**error** **correction**” reflects the **correction** on the long-run relationship by the short-run dynamics.

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series analyses. Most of the studies on the MENA economies failed to pre-test for unit roots, to determine the optimal length of lags and/or to apply cointegration tests and **error** **correction** models when testing for causality. Unless otherwise stated, most of the studies surveyed below failed to apply cointegration tests to detect long-run relationship between exports and economic growth. In the presence of cointegrated series, inferences based on the SGC are inappropriate (Granger, 1988). The few studies that adopted cointegration tests chose to use the EG test rather than the Johansen test, which is known to be more reliable. Our aim is to employ the latest econometric techniques and the most up-to-date data to examine the causal relationship between exports and economic growth in selected MENA economies. In this way we hope to provide some guidelines to policymakers for fostering economic growth and lessen the volatility of the economic activity in the MENA region.

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For example, in case 1 where the Fisher parity is tested for U.S. data, the hypothesis is that inflation expectations rule the nominal interest rates. In the econometric **model**, the expectations are replaced by current inflation which is viewed as a predictor of unobservable inflation expectations. Obviously and inde- pendent of the specific **model**, the null hypothesis that inflation does not adjust to deviations from the long-run equilibrium is strongly rejected. At the same time, however, it is found that interest rates do not adjust significantly. While the latter statement was found to be true at the 10 percent level only, the situation is much clearer in the Swiss case (example 2). Here, the hypothesis that interest rates do not adjust cannot be rejected at the 18 percent level.

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With the help of the **error** **correction** **model** (ECM) and vector- **error** **correction** (VEC), this articles examines the principal relation- ship between the export volumes of metal products (raw materials component), the export-import products of mechanical engineering (technological component), and industrial production in Ukraine. Its immediate aim is to describe the impact of technological exports on the dynamics of industrial production and the dependence of both indicators on a number of external and internal factors, such as Ukraine’s currency exchange rate and the budget balance. The arti- cle innovatively designs a structural **model** of technological exports (with allowance for short- and long-term trends) and provides em- pirical verification of the dependence of the selected endogenous variable on a broad spectrum of factors (exchange rate, budget bal- ance, aggregated GDP of the countries-trading partners, world prices of metal, and the like).

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Licensed under Creative Common Page 112 adjusted coefficient of determination values turned out to be less than the D-W statistic. Similarly, the F-statistic value was observed to be less than 0.05% implying that the **model** as a whole is significant. Furthermore, the D-W statistic value of 2.4024 is an indication that serial correlation is not likely to be an issue in the **model**, since it is very close to 2. The adjusted coefficient of determination value of 0.325 implies that approximately 33% of the systematic changes in economic growth in Namibia have been explained by the variables included in the **error** **correction** **model**. Presumably, the explanatory variables used in the **error** **correction** **model** are not good predictors of economic growth in Namibia.

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For all these reasons, it is brought to us that domestic investments are among the best needful settlements for saving and reducing most of these disasters of this country. For this purpose, we attempt to treat the contribution of domestic investment on economic growth for the case of the Uruguayan economy over the period 1960-2017 by applying the Vector **Error** **Correction** **Model** (VECM). To the best of our knowledge, none of the previous studies investigate the impact of domestic investment on growth in Uruguay.

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Vector AutoRegression technique cannot be applied to the four Return(i,t) series because the four Return(i,t) series are cointegrated; that is, the four Return(i,t) series follow the same long-run trend, but the short-run trend is random. There are eight options for running the VEC **model**. The VEC **model** can be run with no trend in the VEC but with an intercept included or not. The VEC **model** can be run with a trend in the VEC and an intercept and/or a trend in the cointegration equation. The vector **error** **correction** equation uses lagged deviations for each of the four Return(i,t) series as independent variables for each of the four Return(i,t) series in a regression that also include lagged deviation variables for each of the four Return(i,t) series. Each set of VEC estimated regression includes the cointegrating equation plus a series of deviations from past changes in the four Return(i,t) series with up to two lags, unless more lags are specified. In addition, each VEC analysis can include a trend in the VEC and/or an intercept or a trend for each VEC. Table 10 contains the empirical results for the VEC **model** with a trend in the data and both an intercept and a trend in the **error** **correction** **model**. Given that the four Return(i,t) series are constructed with an intercept and a trend, the **model** with a trend in the data and a VEC **model** with both an intercept and a trend would seem to be most appropriate. The empirical results for this **model** show that the **error** **correction** equation is statistically significant but the trend is not statistically significant because the regression **model** accounts for the long-run trend effect across the four Return(i,t) series. Although the **error** **correction** variables are mostly statistically significant, the signs are random. This supports the hypothesis that cointegration is statistically significant but random in effect. The other three models provide similar results.

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