scholarly journals Tinjauan terhadap Metode Ekonometrika Lanjutan

2003 ◽  
Vol 4 (1) ◽  
pp. 59-74
Author(s):  
Telisa Aulia Falianty
Keyword(s):  
Genetic Algorithm ◽  
Time Series ◽  
Panel Data ◽  
Unit Root ◽  
Time Series Data ◽  
Random Effect ◽  
Unit Root Test ◽  
Cointegration Analysis ◽  
Series Data ◽  
Theory Of Evolution

Econometric models have been played an increasingly important role in empirical analysis in economics. This paper provides an overview on some advanced econometric methods that increasingly used in empirical studies.A panel data combines features of both time series and cross section data. Because of increasing availability of panel data in economic sciences, panel data regression models are being increasingly used by researcher. Related to panel data model, there are some methods that will be discussed here such as fixed effect and random effect. A new approach to panel data that developed by Im, Shin, and Pesaran (2002) for testing unit root in heterogenous panel is included in this overview.When we work with time series data, there are many problems that we must handle, most of them are unit root test, cointegration among non stationary variables, and autoregressive conditional heteroscedasticity. Provided these problems, author also review about ADF and Philips-Perron test. An approch to cointegration analysis developed by Pesaran (1999), ARCH and GARCH model are also interesting to be discussed here.Bayesian econometric, that less known than classical econometric, is includcd in this overview. The genctic algorithm, a relatively new method in econometric, has bcen increasingly employed the behavior of economic agents in macroeconomic models. The genetic algorithm is based on thc process of Darwin’s Theory of Evolution. By starting with a set of potential solutions and changing them during several iterations, the Genetic Algorithm hopes to converge on the most ‘fit’ solutions.

scholarly journals Economic Growth, Inflation and Monetary Policy in Pakistan: Preliminary Empirical Estimates

2021 ◽  
Vol 4 (2) ◽  
pp. 321-333
Author(s):  
Hina Ali ◽  
Malka Liaquat ◽  
Noreen Safdar ◽  
Saeed ur Rahman
Keyword(s):  
Time Series ◽  
Monetary Policy ◽  
Unit Root ◽  
Time Series Data ◽  
Unit Root Test ◽  
Series Data ◽  
Economic Activities ◽  
Data Set ◽  
Explanatory Variables ◽  
Empirical Estimates

In economic policy, construction Inflation is a core variable to be considered that determines the economic activity. To make a suitable monetary policy, it is very essential to check the price level and later on, many other variables are considered to achieve the goal. This study aims to reveal the affiliation of inflation on the growth of economic activities in Pakistan. Time series data set for the period 1989-2020 was used to have the empirical estimates.  Augmented Dickey Fuller Unit Root Test is employed to check the unit root of the time series and Auto Regressive Distributive Lag techniques are used for empirical estimates. The present research uses Inflation as a dependent variable and Gross Domestic Product, Interest Rate, Money Supply, and Exchange Rate as the explanatory variables of the study. The findings of this analysis reveal that there's an antagonistic relation between Inflation and GDP.

UNIT ROOT TESTS IN THE PRESENCE OF MULTIPLE BREAKS IN VARIANCE

2017 ◽  
Vol 62 (02) ◽  
pp. 345-361
Author(s):  
SOO-BIN JEONG ◽  
BONG-HWAN KIM ◽  
TAE-HWAN KIM ◽  
HYUNG-HO MOON
Keyword(s):  
Time Series ◽  
Unit Root ◽  
Time Series Data ◽  
Unit Root Test ◽  
Unit Root Tests ◽  
Series Data ◽  
Simulation Experiments ◽  
Innovation Variance ◽  
Multiple Breaks

Spurious rejections of the standard Dickey–Fuller (DF) test caused by a single variance break have been reported and some solutions to correct the problem have been proposed in the literature. Kim et al. (2002) put forward a correctly-sized unit root test robust to a single variance break, called the KLN test. However, there can be more than one break in variance in time series data as documented in Zhou and Perron (2008), so allowing only one break can be too restrictive. In this paper, we show that multiple breaks in variance can generate spurious rejections not only by the standard DF test but also by the KLN test. We then propose a bootstrap-based unit root test that is correctly-sized in the presence of multiple breaks in variance. Simulation experiments demonstrate that the proposed test performs well regardless of the number of breaks and the location of the breaks in innovation variance.

scholarly journals Does Foreign Direct Investment and Trade Promote Economic Growth? Evidence from Albania

Economies ◽  
2021 ◽  
Vol 9 (1) ◽  
pp. 1
Author(s):  
Sam Hobbs ◽  
Dimitrios Paparas ◽  
Mostafa E. AboElsoud
Keyword(s):  
Economic Growth ◽  
Foreign Direct Investment ◽  
Granger Causality ◽  
Unit Root ◽  
Direct Investment ◽  
Time Series Data ◽  
Unit Root Test ◽  
Global Market ◽  
Cointegration Analysis ◽  
Series Data

Albania has experienced a rapid transition from a centrally planned economy to a mixed economy since the fall of communism in 1989. Policy changes, trade liberalization, and privatization have come about at a rapid pace, allowing foreign direct investment (FDI) and international trade to become key components of Albania’s economy. Against this backdrop, this study investigates the relationships among FDI, trade, and economic growth in Albania. Annual time-series data were obtained from the World Bank. Then, the following econometric tests were performed on the variables representing FDI inflows, exports, and GDP as proxies for FDI, trade, and economic growth: the unit root test; the unit root test with a structural break; Johansen cointegration analysis; the error correction model; and the Granger causality test. The results revealed a long-term relationship between FDI, trade, and economic growth. The Granger causality tests found unidirectional causality. Economic growth brought about exports and FDI in the short term but not vice versa. In conclusion, policymakers need to design policies that promote technology-based, export-promoting FDI to meet the needs of the economy and develop specialized sectors that are competitive in the global market. Furthermore, the salient takeaway is that the penetration of export markets should be promoted as much as the furtherance of FDI.

scholarly journals ARDL as an Elixir Approach to Cure for Spurious Regression in Nonstationary Time Series

Mathematics ◽  
2021 ◽  
Vol 9 (22) ◽  
pp. 2839
Author(s):  
Ghulam Ghouse ◽  
Saud Ahmad Khan ◽  
Atiq Ur Rehman ◽  
Muhammad Ishaq Bhatti
Keyword(s):  
Time Series ◽  
Unit Root ◽  
Time Series Data ◽  
Cointegration Analysis ◽  
Series Data ◽  
Testing Procedures ◽  
Spurious Regression ◽  
Distributed Lag ◽  
Autoregressive Distributed Lag ◽  
Unit Root Testing

In conventional Econometrics, the unit root and cointegration analysis are the only ways to circumvent the spurious regression which may arise from missing variable (lag values) rather than the nonstationarity process in time series data. We propose the Ghouse equation solution of autoregressive distributed lag mechanism which does not require additional work in unit root testing and bound testing. This advantage makes the proposed methodology more efficient compared to the existing cointegration procedures. The earlier tests weaken their position in comparison to it, as they had numerous linked testing procedures which further increase the size of the test and/or reduce the test power. The simplification of the Ghouse equation does not attain any such type of error, which makes it a more powerful test as compared to widely cited exiting testing methods in econometrics and statistics literature.

scholarly journals KOINTEGRASI DAN KAUSALITAS INDEKS HARGA SAHAM GABUNGAN DAN DOW JONES INDUSTRIAL INDEX

2016 ◽  
Vol 4 (2) ◽  
Author(s):  
Paulus Sulluk Kananlua
Keyword(s):  
Time Series ◽  
Impulse Response ◽  
Unit Root ◽  
Time Series Data ◽  
Global Financial Crisis ◽  
Unit Root Test ◽  
Variance Decomposition ◽  
Cointegration Test ◽  
Series Data ◽  
The Impact

This research is obviously intended to analyze the impact of global financial crisis which happened in America and surrogated by the Dow Jones Industrial Index (DJI) towards the Indonesian Stock Exchange, represented by the composite index (IHSG). The study is conducted by using time series data ranging from January 2007 to July 2014. Data used consists of 60 months observation. In order to examine the time series data, Vector Autoregressive Model (VAR) is employed. We run the statistical tool to estimate the respon caused by the shock of research variable. Before estimating the model of Vector Autoregression (VAR), the data used must following the unit root test, cointegration test, granger causality test, and then runned by using VAR model. Our result reveals that the data is not stationer at level, but stationer at first difference. The interpreted estimation output resulting from impulse response function and variance decomposition show that DJI’s respons is much bigger caused by the shock from DJI itself with average number stand on 99.36%. Further, the proportion of IHSG on average is 0.64%. Meanwhile the respon of IHSG sparked by the DJI is 53.10% on average. The remained value as 46.90% is caused by the shock from IHSG.  Key Words: DJI, IHSG, VAR, Unit Root Test, Cointegration Test, Granger Test, Impulse Response,Variance Decomposition

scholarly journals Import Flows of Bangladesh: Gravity Model Approach under Panel Data Methodology

2012 ◽  
Vol 60 (2) ◽  
pp. 153-157 ◽  
Author(s):  
Mili Roy ◽  
Md. Israt Rayhan
Keyword(s):  
Panel Data ◽  
Gravity Model ◽  
Cross Section ◽  
Time Series Data ◽  
Random Effect ◽  
Least Square ◽  
Series Data ◽  
Ordinary Least Square ◽  
Extended Gravity ◽  
Trading Partners

In counterpoint to export growth, Bangladesh import growth has remained much less strong, despite impressive progress in import liberalization. This study gives an overview of different methodologies related to gravity model analysis in Bangladesh’s import flow. A pooled cross section and time series data were analyzed to incorporate the country specific heterogeneity in country pair trading partners. The import flows are justified by the basic gravity model since Bangladesh’s imports are positively significant by the economy size and inversely related to trade barrier. Accordingly, we have analyzed pooled ordinary least square, fixed effect, random effect. This study also explores extended gravity model using several variables in the light of gravity model panel data approach. Bangladesh’s import is determined by the home and foreign country’s gross domestic product and exchange rate. In addition, Cross section results show that regional trade arrangement which is South Asian Association for Regional Co-operation and border are significant for Bangladesh’s importimplies that Bangladesh should import more from intra regional country and also should import from India.DOI: http://dx.doi.org/10.3329/dujs.v60i2.11485 Dhaka Univ. J. Sci. 60(2): 153-157, 2012 (July)  

scholarly journals ESTIMATION OF AUTOREGRESSIVE ROOTS NEAR UNITY USING PANEL DATA

2000 ◽  
Vol 16 (6) ◽  
pp. 927-997 ◽  
Author(s):  
Hyungsik R. Moon ◽  
Peter C.B. Phillips
Keyword(s):  
Time Series ◽  
Panel Data ◽  
Time Series Data ◽  
Initial Conditions ◽  
Series Data ◽  
Test Statistics ◽  
Rate Condition ◽  
Panel Models ◽  
Stochastic Trends ◽  
Efficient Extraction

Time series data are often well modeled by using the device of an autoregressive root that is local to unity. Unfortunately, the localizing parameter (c) is not consistently estimable using existing time series econometric techniques and the lack of a consistent estimator complicates inference. This paper develops procedures for the estimation of a common localizing parameter using panel data. Pooling information across individuals in a panel aids the identification and estimation of the localizing parameter and leads to consistent estimation in simple panel models. However, in the important case of models with concomitant deterministic trends, it is shown that pooled panel estimators of the localizing parameter are asymptotically biased. Some techniques are developed to overcome this difficulty, and consistent estimators of c in the region c < 0 are developed for panel models with deterministic and stochastic trends. A limit distribution theory is also established, and test statistics are constructed for exploring interesting hypotheses, such as the equivalence of local to unity parameters across subgroups of the population. The methods are applied to the empirically important problem of the efficient extraction of deterministic trends. They are also shown to deliver consistent estimates of distancing parameters in nonstationary panel models where the initial conditions are in the distant past. In the development of the asymptotic theory this paper makes use of both sequential and joint limit approaches. An important limitation in the operation of the joint asymptotics that is sometimes needed in our development is the rate condition n/T → 0. So the results in the paper are likely to be most relevant in panels where T is large and n is moderately large.

scholarly journals Purchasing Power Parity in Commonwealth of Independent States

2014 ◽  
Author(s):  
Gülçin Güreşçi Pehlivan ◽  
Esra Ballı ◽  
Muammer Tekeoğlu
Keyword(s):  
Time Series ◽  
Panel Data ◽  
Cross Section ◽  
Purchasing Power Parity ◽  
Unit Root ◽  
Unit Root Test ◽  
Purchasing Power ◽  
Power Parity ◽  
Panel Unit Root ◽  
Independent States

The Purchasing Power Parity suggests that differences in relative prices in two countries move together with nominal exchange rates in the long run. This study examines the validity of PPP as transition economies for Commonwealth of Independent States (CIS). Purchasing Power Parity holds only when the real exchange rate is stationary in the equation. To test the stationary, we used both time series and panel data analysis. Testing unit root both with time series and panel data in this study, provides us double check of the results. We also test the cross sectional dependence to choose the appropriate panel unit root test. Our test statistics indicate that there is cross section dependence between countries. Hence, one needs to take into consideration the cross section dependence while undertaking unit root tests. Otherwise, the results would be biased. ADF and KPPS indicate that PPP cannot be accepted for the countries except for Russia. According to the panel unit root test results indicate that PPP does not hold for Armenia, Belarus, Georgia, Kazakhstan and Kyrgyzstan except for Russia.

scholarly journals Consumer Spending and Consumer Confidence in South Africa: Cointegration Analysis

2014 ◽  
Vol 6 (2) ◽  
pp. 95-104
Author(s):  
John Khumalo
Keyword(s):  
Economic Growth ◽  
South Africa ◽  
Unit Root ◽  
Time Series Data ◽  
Positive Impact ◽  
Cointegration Analysis ◽  
Consumer Confidence ◽  
Series Data ◽  
Consumer Spending ◽  
Long Run

The study uses the time series data covering the period 1980Q1 to 2012Q3 to test the existence of any possible long run relationship between consumer spending and consumer confidence in South Africa. The analysis is done using the Vector Auto-Regressive (VAR) model, with the unit root and the direction of causation also tested before any inference can be concluded on this relationship. The unit root tests using the DF-GLS as well as the Ng-Peron show that consumer spending, consumer confidence and economic growth are integrated of order zero ~I(0). Causality results on the other hand reveal that causation runs from consumer confidence to consumer spending and from economic growth to consumer spending in South Africa. The non-existence of unit root compels the establishment of the long-run relationship that leads us to performing VECM to establish short-run and long-run dynamics. Our results indicate that the positive effect of consumer confidence cannot be refuted in South Africa and that it exerts a significant and positive impact on consumer spending, hence aggregate spending.

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