Introduction to Symposium on Time Series Error Correction Methods in Political Science

2016 ◽  
Vol 24 (1) ◽  
pp. 1-2 ◽  
Author(s):  
Janet Box-Steffensmeier ◽  
Agnar Freyr Helgason
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Error Correction ◽  
Political Science ◽  
Time Series Data ◽  
Series Data ◽  
Correction Model ◽  
Methodological Choices ◽  
Made In ◽  
General Error

In recent years, political science has seen a boom in the use of sophisticated methodological tools for time series analysis. One such tool is the general error correction model (GECM), originally introduced to political scientists in the pages of this journal over 20 years ago (Durr 1992; Ostrom and Smith 1992) and re-introduced by De Boef and Keele (2008), who advocate its use for a wider set of time series data than previously considered appropriate. Their article has proven quite influential, with numerous papers justifying their methodological choices with reference to De Boef and Keele's contribution.Grant and Lebo (2016) take issue with the increasing use of the GECM in political science and argue that the methodology is widely misused and abused by practitioners. Given the recent surge of research conducted using error correction methods, there is every reason to take their suggestions seriously and provide a fuller discussion of the points they raise in their paper. The present symposium serves such a role. It consists of Grant and Lebo's critique, a detailed response by Keele, Linn, and Webb (2016b), and shorter comments by Esarey (2016), Freeman (2016), and Helgason (2016). Finally, Lebo and Grant (2016) and Keele, Linn, and Webb (2016a) reflect on the contributions made in the symposium, as well as discuss outstanding issues.

scholarly journals Moving forward with time series analysis

2017 ◽  
Vol 4 (4) ◽  
pp. 205316801773223
Author(s):  
Peter K. Enns ◽  
Nathan J. Kelly ◽  
Takaaki Masaki ◽  
Patrick C. Wohlfarth
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Error Correction ◽  
Time Series Data ◽  
Error Correction Model ◽  
Series Data ◽  
Correction Model ◽  
Standard Procedures ◽  
Cointegration Tests ◽  
General Error

In a recent Research and Politics article, we showed that for many types of time series data, concerns about spurious relationships can be overcome by following standard procedures associated with cointegration tests and the general error correction model (GECM). Matthew Lebo and Patrick Kraft (LK) incorrectly argue that our recommended approach will lead researchers to identify false (i.e., spurious) relationships. In this article, we show how LK’s response is incorrect or misleading in multiple ways. Most importantly, when we correct their simulations, their results reinforce our previous findings, highlighting the utility of the GECM when estimated and interpreted correctly.

scholarly journals The Long-Run and Short-Run Impacts of Investment, Export, Money Supply, and Inflation on Economic Growth In Indonesia

2019 ◽  
Vol 22 (1) ◽  
Author(s):  
Erni Panca Kurniasih
Keyword(s):  
Economic Growth ◽  
Time Series ◽  
Error Correction ◽  
Money Supply ◽  
Time Series Data ◽  
Error Correction Model ◽  
Series Data ◽  
Correction Model ◽  
Long Run ◽  
Short Term Investment

ABSTRACTThe development of investment and exports in Indonesia shows an increase, as well as money supply, while the inflation rate shows a decline, but this is not always followed by increasing economic growth. This study aims to explain the relationship between investment, export, money supply and inflation with the economic growth in Indonesia. The data used was time series data from the first quarter in 2001 to the fourth quarter in 2014 and was analyzed using multiple regression models with Error Correction Model (ECM) and classical assumptions. The study findings show that in short-term investment, export, money supply and inflation are not significant to economic growth. In long-run, investment has negative and significant effect on the economic growth, while export, money supply and inflation have positive and significant effect on the economic growth in Indonesia. Bank Indonesia must applied a tight money policy consistently to achieve the long-term inflation target ABSTRAKPerkembangan investasi dan ekspor di Indonesia menunjukkan peningkatan, demikian pula jumlah uang beredar, sementara tingkat inflasi menunjukkan penurunan, namun hal tersebut tidak selalu diikuti dengan meningkatnya pertumbuhan ekonomi. Studi ini bertujuan untuk menjelaskan hubungan antara investasi, ekspor neto, jumlah uang beredar dan inflasi terhadap pertumbuhan ekonomi di Indonesia. Data yang digunakan adalah data time series dari kuartal pertama tahun 2001 hingga kuartal keempat tahun 2014 dan dianalisa dengan menggunakan model regresi berganda dengan Error Correction Model (ECM). Hasil studi menunjukkan  bahwa investasi, ekspor, jumlah uang beredar dan inflasi tidak signifikan terhadap pertumbuhan ekonomi di Indonesia dalam jangka pendek. Investasi berpengaruh negatif dan signifikan terhadap pertumbuhan ekonomi di Indonesia dalam jangka panjang, sedangkan ekspor , jumlah uang beredar dan inflasi berpengaruh positif dan  signifikan terhadap pertumbuhan ekonomi di Indonesia. Bank Indonesia harus menerapkan kebijakan moneter yang ketat secara konsisten pada pencapaian sasaran inflasi jangka menenngah 

scholarly journals SPURIOUS REGRESSION ANALYSIS ON TIME SERIES DATA FROM FACTORS AFFECTING INDONESIAN HUMAN DEVELOPMENT INDEXS IN 1990 – 2017

2021 ◽  
Vol 7 (3) ◽  
Author(s):  
Rinto Rain Barry ◽  
Innocentius Bernarto
Keyword(s):  
Time Series ◽  
Error Correction ◽  
Human Development ◽  
Time Series Data ◽  
Series Data ◽  
Correction Model ◽  
Independent Variables ◽  
Spurious Regression ◽  
Equilibrium Relationship

In a spurious regression conditions occur linear regression equations that are not stationary on the mean and variance. If the variables are not stationary, there will be cointegration, so it can be concluded that there is a long-term equilibrium relationship between the two research variables and in the short term there is a possibility of an imbalance, so to overcome it in this study using the Error Correction Model. The purpose of this study is to apply a cointegration test to see whether there is a long-term non-equilibrium relationship between the time series between the Human Development Index and life expectancy at birth, average school year for adults aged 25 years and over and gross national income per capita. The data used in this study are time series data between 1990-2017. The statistical management is carried out using Eviews 10. Based on the results obtained, it was concluded that 81.7% and it can be said that the types of independent variables included in the model are already good, because only 18.3% of the diversity of the dependent variable is influenced by the independent variables outside this research model. Keywords: spurious regression, stationary, cointegration, error correction model, equilibrium

Error Correction Methods with Political Time Series

2016 ◽  
Vol 24 (1) ◽  
pp. 3-30 ◽  
Author(s):  
Taylor Grant ◽  
Matthew J. Lebo
Keyword(s):  
Time Series ◽  
Sample Size ◽  
Error Correction ◽  
Political Science ◽  
Correction Model ◽  
Long Run ◽  
Size Number ◽  
Political Time ◽  
True Time ◽  
General Error

While traditionally considered for non-stationary and cointegrated data, DeBoef and Keele suggest applying a General Error Correction Model (GECM) to stationary data with or without cointegration. The GECM has since become extremely popular in political science but practitioners have confused essential points. For one, the model is treated as perfectly flexible when, in fact, the opposite is true. Time series of various orders of integration–stationary, non-stationary, explosive, near- and fractionally integrated–should not be analyzed together but researchers consistently make this mistake. That is, withoutequation balancethe model is misspecified and hypothesis tests and long-run-multipliers are unreliable. Another problem is that the error correction term's sampling distribution moves dramatically depending upon the order of integration, sample size, number of covariates, and theboundednessofYt.This means that practitioners are likely to overstate evidence of error correction, especially when using a traditionalt-test. We evaluate common GECM practices with six types of data, 746 simulations, and five paper replications.

scholarly journals PROFITABILITY OF ISLAMIC MICROFINANCE IN INDONESIA: DOES THE TYPE OF FINANCING MATTER?

2021 ◽  
Vol 1 (1) ◽  
pp. 31-38
Author(s):  
Chitra Yuliashri Katili ◽  
Rifadli D. Kadir
Keyword(s):  
Time Series ◽  
Error Correction ◽  
Significant Influence ◽  
Time Series Data ◽  
Error Correction Model ◽  
Series Data ◽  
Correction Model ◽  
Islamic Microfinance

This study aims to examine the effect of Inflation Variables, CAR, NPF, Murabahah Financing, Mudharabah Financing, and Musyarakah Financing on the Profitability of Sharia BPRs in Indonesia. This study uses time series data from 2016-2020. The data is processed using the Error Correction Model (ECM). This study concludes that Murabahah Financing Variables have a significant influence and other variables, namely Inflation, CAR, NPF, Mudharabah Financing and Musyarakah Financing have no effect on the Profitability of Sharia BPRs in Indonesia. Thus, the type of financing affects the profitability of Sharia BPR in Indonesia

scholarly journals Analisis Pengeluaran Sektor Pariwisata terhadap Ketimpangan Upah Tenaga Kerja di Indonesia

2019 ◽  
pp. 100-118
Author(s):  
Lalu Muhammad Azmi Prasetya ◽  
M. Pudjihardjo ◽  
Nurul Badriyah
Keyword(s):  
Time Series ◽  
Error Correction ◽  
Wage Inequality ◽  
Foreign Investment ◽  
Time Series Data ◽  
Government Expenditure ◽  
Error Correction Model ◽  
Series Data ◽  
Correction Model ◽  
Foreign Tourist

This study analyses the effect of foreign tourist expenditure, government expenditure and foreign investment on wage inequality between skilled, semi-skilled and unskilled labour in the Indonesian tourism sector. The study uses time series data with a period of 22 years. The method used is Error Correction Model (ECM). The results of this study indicate that foreign tourist expenditure and government expenditure increase inequality in the short term, but in the long run can reduce wage inequality. Meanwhile, foreign investment increases inequality both in the short and long term. ================================ Penelitian ini menganalisis pengaruh pengeluaran wisatawan mancanegara, pengeluaran pemerintah dan investasi asing terhadap ketimpangan upah antara tenaga kerja terampil, semi terampil, dan tidak terampil di sektor pariwisata Indonesia. Penelitian menggunakan data time series dengan periode waktu 22 tahun. Metode yang digunakan adalah Error Correction Model (ECM). Hasil penelitian ini menunjukkan bahwa pengeluaran wisatawan dan pemerintah meningkatkan ketimpangan dalam jangka pendek, namun dalam jangka panjang mampu menurunkan ketimpangan upah. Investasi asing meningkatkan ketimpangan, baik dalam jangka pendek maupun jangka panjang.

Analisis Kekakuan dan Faktor-faktor yang Memengaruhi Tingkat Suku Bunga Perbankan di Indonesia

2013 ◽  
Vol 8 (2) ◽  
pp. 26
Author(s):  
Eko Listiyanto ◽  
Telisa Aulia Falianty
Keyword(s):  
Time Series ◽  
Interest Rate ◽  
Interest Rates ◽  
Error Correction ◽  
Time Series Data ◽  
Error Correction Model ◽  
Least Square ◽  
Capital Adequacy ◽  
Series Data ◽  
Correction Model

<p align="center"><em>ABSTRACT</em></p><p><em>The research discusses the rigidity of interest rates on deposits and loans to changes in interest rate policies in the three groups of banks in Indonesia, and the factors that influence the interest rates on deposits and loans in the banking system. Rigidity of bank interest rates were analyzed with error correction model approach (Error Correction Model / ECM) using panel data. While the factors that influence the development of the banking interest rates were analyzed with multiple linear regression approach method of Generalized Least Square (GLS) using time series data. The period of data used from July 2005-March 2010.</em></p><p><em>Error Correction Model shows the slackness of interest rates response on deposits and loans toward the policy of interest rate. The rigidity of interest rates on deposits and loans in Indonesia is relatively slow when compared to some other countries.</em></p><p><em>Regression results with GLS method proves that the banking efficiency factor, bad credit and market share significantly influence the interest rates on deposits. While the borrowing rate is influenced by the rate of inflation, capital adequacy ratio, as well as bad credit. The results of this study suggest the importance of watching bad credit factors in making monetary policy because it can affect the interest rates on deposits and lending interest rates.  </em></p><p>ABSTRAK</p><p>Penelitian ini membahas kekakuan suku bunga deposito dan pinjaman untuk perubahan kebijakan suku bunga dalam tiga kelompok bank di Indonesia, dan faktor-faktor yang mempengaruhi suku bunga deposito dan pinjaman dalam sistem perbankan. Kekakuan suku bunga perbankan dianalisis dengan pendekatan error correction model (Error Correction Model / ECM) menggunakan data panel. Sedangkan faktor-faktor yang mempengaruhi perkembangan suku bunga perbankan dianalisis dengan metode pendekatan regresi linier berganda dari Generalized Least Square (GLS) dengan menggunakan data time series. Periode data yang digunakan dari Juli 2005-Maret 2010.</p><p>Error Correction Model menunjukkan kelambanan dari suku bunga respon deposito dan pinjaman terhadap kebijakan tingkat suku bunga. Kekakuan suku bunga deposito dan pinjaman di Indonesia relatif lambat jika dibandingkan dengan beberapa negara lain.</p><p>Hasil regresi dengan metode GLS membuktikan bahwa faktor efisiensi perbankan, kredit macet dan pangsa pasar secara signifikan mempengaruhi suku bunga deposito. Sementara tingkat pinjaman dipengaruhi oleh tingkat inflasi, rasio kecukupan modal, serta kredit macet. Hasil penelitian ini menunjukkan pentingnya menonton faktor kredit macet dalam membuat kebijakan moneter karena dapat mempengaruhi suku bunga deposito dan suku bunga kredit.</p>

scholarly journals PENGARUH GUNCANGAN OUTPUT GAP DAN INFLASI TERHADAP SUKU BUNGA SEBAGAI SASARAN OPERASIONAL KEBIJAKAN MONETER DI INDONESIA

2012 ◽  
Vol 1 (2) ◽  
Author(s):  
Utami Baroroh
Keyword(s):  
Time Series ◽  
Interest Rate ◽  
Error Correction ◽  
Time Series Data ◽  
Series Data ◽  
Output Gap ◽  
Vector Error Correction Model ◽  
Correction Model ◽  
Vector Error Correction ◽  
Vector Error

The objectives of this study are to observe interest rate response because shock/innovation of inflation and output gap. The data sample used in this study are quarterly time series data from 1983.1 – 2008.4. Those data are SBI interest rate, inflation (CPI) and output gap. A method of analysis in this study is Vector Error Correction Model (VECM). The empirical results of impulse response show that the effect of inflation and output gap shock to interest rate is positifDOI: 10.15408/sjie.v1i2.2601

scholarly journals PENDUGAAN FUNGSI PENAWARAN EKSPOR RUMPUT LAUT INDONESIA DI PASAR INTERNASIONAL Analisis Pendekatan Error Correction Model (ECM)

2017 ◽  
Vol 3 (1) ◽  
pp. 55
Author(s):  
Risna Yusuf ◽  
Tajerin Tajerin
Keyword(s):  
Time Series ◽  
Error Correction ◽  
Time Series Data ◽  
Export Price ◽  
International Market ◽  
Error Correction Model ◽  
Series Data ◽  
Correction Model ◽  
Export Supply ◽  
The Government

Kajian ini bertujuan untuk menduga faktor-faktor yang mempengaruhi penawaran ekspor rumput laut Indonesia di pasar Internasional dengan menggunakan data runut waktu (time series data) tahun 1975 hingga 2005. Pendugaan persamaan penawaran ekspor rumput laut tersebut dilakukan dengan pendekatan metoda koreksi kesalahan (Error Corection Model – ECM). Hasil analisis menunjukkan bahwa penawaran ekspor rumput laut Indonesia ke pasar internasional dipengaruhi oleh produksi, harga ekspor, pendapatan nasional bruto negara mitra dagang, nilai tukar rupiah dan ekspor rumput laut Indenesia tahun lalu dengan arah perubahan yang sama (positif), dan harga domestik dan tingkat suku bunga dengan arah perubahan yang berlawanan (negatif). Oleh karena itu, perlu kesungguhan pemerintah bersama nelayan/pembudidaya & eksportir rumput laut untuk menjaga mutu; dan lebih meningkatkan kerjasama perdagangan dengan negara mitra dagang Indonesia (Importir), demikian juga dengan negara produsen lainnya. Tittle: The Estimation of Indonesian Seaweed Export Supply Function in the International Market : Analysis of Error Correction Model (ECM)The aim of the research was to estimate the factors affecting Indonesian seaweed export supply in international market using secondary time series data from 1975 until 2005. The estimation of supply was done using error correction model (ECM). The results show that export supply of Indonesian seaweed in international markets is affected by production, export price, gross national product, exchange rate, and lagged export of Indonesian seaweed which all have positive signs. On the other hand domestic price and interest rate have negative signs. Therefore, the government, fishers/seaweed farmers and seaweed exporter must pay more attention on seaweed quality and trade cooperation with importer and other producers.

scholarly journals Analyzing The Macroeconomic and Fundamental Determinants of Non-Performing Financing of Bank Muamalat Indonesia

2020 ◽  
Vol 11 (1) ◽  
pp. 49-78
Author(s):  
Pungky Lela Saputri ◽  
Ratno Agriyanto ◽  
Mujiyono Abdillah
Keyword(s):  
Time Series ◽  
Error Correction ◽  
Time Series Data ◽  
Error Correction Model ◽  
Capital Adequacy ◽  
Series Data ◽  
Islamic Banking ◽  
Correction Model ◽  
Long Run ◽  
Short Run

Abstract: This study analyzes the macroeconomic and fundamentals of Islamic banking factors towards the non-performing financing (NPF) of Bank Muamalat Indonesia in the long run and short-run period 2005-2018. The data used in this study are quarterly time-series data of Bank Muamalat Indonesia Financial Report as the source of fundamentals of Islamic banking data and Bank Indonesia Monetary Policy Review as the source of macroeconomic data period 2005 - 2018. The analytical method used is the Error Correction Model (ECM). This study shows that in the long run, inflation, central bank (Bank Indonesia/BI) Rate, and capital adequacy ratio (CAR) significantly affect the NPF; meanwhile, the financing to deposit (FDR) ratio does not affect NPF. In the short term context, only CAR has a significant effect, yet inflation, BI Rate, and FDR have no significant impact on NPF. Thus, the novelty can present the result of analysis of factors that affect NPF in the long run and short run. The limitation of the study is the use of time-series data that are very likely to spurious regression.Abstrak: Penelitian ini bertujuan untuk menganalisis pengaruh faktor makroekonomi dan fundamental perbankan syariah terhadap NPF Bank Muamalat Indonesia dalam jangka panjang dan jangka pendek periode 2005-2018. Data yang digunakan dalam penelitian ini yaitu data runtun waktu Laporan Keuangan Triwulan Bank Muamalat Indonesia sebagai sumber data fundamental perbankan syariah dan Tinjauan Kebijakan Moneter Bank Indonesia sebagai sumber data makroekonomi periode 2005 – 2018. Faktor makroekonomi diwujudkan dalam variabel Inflasi dan BI Rate. Faktor fundamental perbankan syariah diwujudkan dalam variabel CAR dan FDR. Alat analisis yang digunakan yaitu Error Correction Model (ECM). Hasil analisis menunjukkan dalam jangka panjang Inflasi, BI Rate, dan CAR dengan nilai signifikansi 0.0026, 0.0001, dan 0.0032 berpengaruh signifikan dan FDR dengan nilai signifikansi 0.6940 tidak berpengaruh signifikan terhadap NPF. Dalam jangka pendek hanya CAR dengan nilai signifikansi 0.0056 yang berpengaruh signifikan sedangkan Inflasi, BI Rate, dan FDR dengan nilai signifikansi 0.0666, 0.9532, and 0.2065 berpengaruh tidak signifikan terhadap NPF. Kebaharuan penelitian ini yaitu penelitian ini mampu menyajikan hasil analisis faktor-faktor yang mempengaruhi NPF dalam jangka panjang dan jangka pendek. Meski begitu, terdapat juga limitasi pada penelitian ini yaitu penggunaan data time series yang rawan terkena regresi lancung.

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