Cointegration Rank Research Articles

Improving Cointegration-Based Pairs Trading Strategy with Asymptotic Analyses and Convergence Rate Filters

AbstractA pairs trading strategy (PTS) constructs a mean-reverting portfolio whose logarithmic value moves back and forth around a mean price level. It makes profits by longing (or shorting) the portfolio when it is underpriced (overpriced) and closing the portfolio when its value converges to the mean price level. The cointegration-based PTS literature uses the historical sample mean and variance to establish their open/close thresholds, which results in bias thresholds and less converged trades. We derive the asymptotic mean around which the portfolio value oscillates. Revised open/close thresholds determined by our asymptotic mean and standard derivations significantly improve PTS performance. The derivations of asymptotic means can be extended to construct a convergence rate filter mechanism to remove stock pairs that are unlikely to be profitable from trading to further reduce trading risks. Moreover, the PTS literature oversimplifies the joint problem of examining a stock pair’s cointegration property and selecting the fittest vector error correction model (VECM). We propose a two-step model selection procedure to determine the cointegration rank and the fittest VECM via the trace and likelihood ratio tests. We also derive an approximate simple integral trading volume ratio to meet no-odd-lot trading constraints. Experiments from Yuanta/P-shares Taiwan Top 50 Exchange Traded Fund and Yuanta/P-shares Taiwan Mid-Cap 100 Exchange Traded Fund constituent stock tick-by-tick backtesting during 2015–2018 show remarkable improvements by adopting our approaches.

MARKET INTEGRATION OF SWEET LIME BETWEEN DOMESTIC AND INTERNATIONAL MARKETS

The study focused on the integration of domestic and international markets for sweet limes during 2021. The co-integration of commodity prices was considered to be necessary for the implementation of a successful marketing reform for which both domestic and international market prices are required. Due to the lack of information regarding international prices, export price information was gathered from thewebsite of the Agricultural and Processed Food Products Export Development Authority (APEDA), and secondary data regarding domestic prices of sweet lime was gathered from the website of the Agricultural Marketing Information Network (AGMARKNET). The annual average prices data for the chosen markets were gathered, and the Pearson correlation coefficient and Johansen’s co-integration analysis approaches were used to analyse the relationship between the chosen market pair. Both markets were found to be correlated through correlation analysis, and the findings of the Johansen Co-integration rank, trace test, and eigen value statistics test were used to analyse the integration among the markets. The study’s findings on market integration reveal how closely related the selected market places’ pricing are to one another. Additionally, this research demonstrated that the model’s variables exhibited an equilibrium longrun co-movement with the market price series.

Dynamic Interaction of Coconut Oil and Crude Oil Prices: Insights from a Vector Error Correction Model

Understanding the relationship between commodity prices is paramount for investors, policymakers, and industries reliant on these markets. This study delves into the intricate dynamics between coconut oil and crude oil prices using a Vector Error Correction Model (VECM). The VECM approach allows for exploring these commodities' short-term adjustments and long-term equilibrium relationships. The analysis reveals that while there may not be a strong long-term interdependence between coconut oil and crude oil prices, robust short-term adjustment mechanisms exist. The cointegration rank two (2) highlights the presence of two cointegrating vectors, indicating a stable equilibrium relationship. The alpha and beta coefficients shed light on the speed and direction of adjustments, emphasizing how the system corrects deviations from the equilibrium relationship. Various model selection criteria, including the Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC), validate the VECM's efficacy in capturing the complexities of these markets while maintaining model simplicity. Moreover, significant error correction terms emphasize the system's self-correcting nature, ensuring long-term stability. Interpreting the coefficients of the lagged terms reveals short-term dynamics, showcasing how coconut oil and crude oil prices mutually influence and respond to changes in one another. The absence of significant autocorrelation in the model's residuals validates the model's accuracy in capturing underlying dynamics.

Inference for the VEC(1) model with a heavy-tailed linear process errors*

This article studies the first-order vector error correction (VEC(1)) model when its noise is a linear process of independent and identically distributed (i.i.d.) heavy-tailed random vectors with a tail index . We show that the rate of convergence of the least squares estimator (LSE) related to the long-run parameters is n (sample size) and its limiting distribution is a stochastic integral in terms of two stable random processes, while the LSE related to the short-term parameters is not consistent. We further propose an automated approach via adaptive shrinkage techniques to determine the cointegrating rank in the VEC(1) model. It is demonstrated that the cointegration rank r 0 can be consistently selected despite the fact that the LSE related to the short-term parameters is not consistently estimable when the tail index . Simulation studies are carried out to evaluate the performance of the proposed procedure in finite samples. Last, we use our techniques to explore the long-run and short-run behavior of the monthly prices of wheat, corn, and wheat flour in the United States.

Adaptive information-based methods for determining the co-integration rank in heteroskedastic VAR models

Standard methods, such as sequential procedures based on Johansen’s (pseudo-)likelihood ratio (PLR) test, for determining the co-integration rank of a vector autoregressive (VAR) system of variables integrated of order one can be significantly affected, even asymptotically, by unconditional heteroskedasticity (non-stationary volatility) in the data. Known solutions to this problem include wild bootstrap implementations of the PLR test or the use of an information criterion, such as the BIC, to select the co-integration rank. Although asymptotically valid in the presence of heteroskedasticity, these methods can display very low finite sample power under some patterns of non-stationary volatility. In particular, they do not exploit potential efficiency gains that could be realized in the presence of non-stationary volatility by using adaptive inference methods. Under the assumption of a known autoregressive lag length, Boswijk and Zu develop adaptive PLR test based methods using a non-parametric estimate of the covariance matrix process. It is well-known, however, that selecting an incorrect lag length can significantly impact on the efficacy of both information criteria and bootstrap PLR tests to determine co-integration rank in finite samples. We show that adaptive information criteria-based approaches can be used to estimate the autoregressive lag order to use in connection with bootstrap adaptive PLR tests, or to jointly determine the co-integration rank and the VAR lag length and that in both cases they are weakly consistent for these parameters in the presence of non-stationary volatility provided standard conditions hold on the penalty term. Monte Carlo simulations are used to demonstrate the potential gains from using adaptive methods and an empirical application to the U.S. term structure is provided.

Model identification via total Frobenius norm of multivariate spectra

Abstract We study the integral of the Frobenius norm as a measure of the discrepancy between two multivariate spectra. Such a measure can be used to fit time series models, and ensures proximity between model and process at all frequencies of the spectral density. We develop new asymptotic results for linear and quadratic functionals of the periodogram, and apply the integrated Frobenius norm to fit time series models and test whether model residuals are white noise. The case of structural time series models is addressed, wherein co-integration rank testing is formally developed. Both applications are studied through simulation studies and time series data. The numerical results show that the proposed estimator can fit moderate- to large-dimensional structural timeseries in real time.

Modeling Gender Life Expectancy Ratio in a Multi-population Framework

AbstractThis paper aims to assess whether the male-to-female ratio in life expectancy is driven by cross-national long-period common trends. If a common trend is detected across a group of countries, then a model taking it into account should provide a more reliable description of the process in scope. We model the gender life expectancy ratio of a set of countries as a multivariate time series. Since our study includes data from 25 countries that are characterized by different longevity patterns, we preliminarily aggregate populations in clusters. Once we verify that all these series are non-stationary, we apply Johansen’s cointegration rank test to each cluster. The idea behind this methodology is to detect any stationary linear combination out of nonstationary variables, which implies that the series share some underlying long-period equilibrium relationships. If the cointegration rank test provides evidence for any cointegrating relationship, we further check whether estimated linear combinations of the single series - namely the error correction terms - are stationary. Finally, we measure forecasting errors with respect to the 10-year testing set. At least for two clusters over six, we find enough evidence to outline some cointegrating relationships in the male-to-female life expectancy ratio. This result leads us to assume that an underlying long-period equilibrium in life expectancy gender differentials does exist among the single countries included in these clusters.

Examination of the Long-run relationship between Human Capital Development and Economic Growth in Nigeria

Abstract: The study explores existence of long run relationship between human capital development and economic growth in Nigeria using secondary data obtained from CBN statistical bulletin for the period of forty years between 1981-2020. The following independent variables were used as the proxies and areas in which human capital could be enhanced and needed to be developed; Agriculture (AGR), Civil-Service (CIVSER), Education (EDU), Health (HLTH), Manufacturing (MANU) and Transportation (TRANSP) sectors of Nigerian economy from 1981 to 2020 as while Gross Domestic Product (GDP) stands for economic growth. The Augmented Dickey-Fuller (ADF) test statistic for ascertaining whether the variables have unit root and Johanson test of co-integration were employed to examine existence of long run relationship between the variables under examination. It was found that variables are stationary at first difference with the level of significance which is 0.0000 for all the variables. The Co-integration of the variables is shown in Tables 3 and 4 where the Unrestricted Co-integration Rank Test (Trace) and Unrestricted Co-integration Rank Test (Maximum Eigen value), respectively, show that the independent variables (all the proxies of Human Capital Development) are co-integrated to determine the dependent variable (GDP which is proxy for economic growth) adjudging that there is long run relationship between human capital development and economic growth.

Analysis and Modeling Gross Domestic Product, Carbon Dioxide Emission, Population Growth, and Life Expectancy at Birth: Case Study in Qatar

Studies on Life Expectancy at Birth (LEB) and Population Growth (PG) with several economic variables for cases in Qatar have not been carried out much. The study of the relationship between Life expectancy at Birth(LEB), Carbon Dioxide(CO2)emission, Population growth(PG), and Gross Domestic Product(GDP)for the case of Qatar is interesting because it is a developed country based on oil and gas. The aims of this study is to build a dynamic model for vector time series that describes the relationship between the variables discussed. From the analysis results based on Criterion Information, Akaike's Information Criterion Correction (AICC), and Cointegration Rank, the best model obtained is the Vector Error Correction Model with order 4 (VECM (4)) and with Cointegration Rank r=4. Based on this dynamic model, Granger-Causality analysis, Impulse Response Function (IRF), and Forecasting will be discussed.

Analysis of Factors Affecting the Import and Consumption of Sugar Cane in Indonesia

This study aims to analyze and determine the effect of (1) production, consumption, price and exchange rate on sugar imports in Indonesia (2) import, production and price of sugar on sugar consumption in Indonesia. This type of research is descriptive and associative. While the type of data is documentary data, the data source is secondary data and time series data from 2000 – 2021. The analysis tool is a simultaneous equation model using the Two Stages Least Squared (TSLS) method. The results of the study concluded that (1) sugar production and exchange rate had no significant effect on sugar imports in Indonesia. While sugar consumption and sugar prices have a significant effect on sugar imports in Indonesia (2) sugar imports have a significant effect on sugar consumption in Indonesia. Meanwhile, production and prices have no significant effect on sugar consumption in Indonesia. From the results of the cointegration test using the Unrestricted Cointegration Rank Test (Trace) approach, it was found that there was a long-term relationship or balance between the variables of sugar production, sugar consumption, sugar imports, sugar prices and the exchange rate. Based on these results, the policy that can be suggested is that the Government through the Ministry of Agriculture should issue policies to encourage the expansion of domestic production scale and improve the quality of sugar in order to suppress imports and at the same time control prices, because large imports will harm sugar farmers and also drain foreign exchange reserves.

FOREIGN DIRECT INVESTMENT AND REAL GROSS DOMESTIC PRODUCT: ANALYSIS OF EMPIRICAL EVIDENCE FROM SRI LANKA

Foreign Direct Investment is one of the crucial forms of international equity flows for having undeniable growth in gross domestic product among emerging countries. The main objective of the study is to investigate the empirical relationship between foreign direct investment and real gross domestic product in Sri Lanka. Net foreign direct inflow was considered as the independent variable while real gross domestic product was considered as the outcome variable in this study. However, Exchange rate and money supply were selected as the control variables on the relationship between foreign direct investment and real gross domestic product. The current study used annual time series data over the period from 1970 to 2019 which were collected from the annual reports of the Central Bank of Sri Lanka. Stationary of the data was tested using the Augmented Dickey-Fuller test. Johansen co-integration rank test, max Eigen value test, Vector Error Correction (VEC) were used to estimate the relationship between foreign direct investment and real gross domestic product. At the 5% level of significance, the co-integration rank test and max Eigen value test revealed that there is only one co-integration equation existing in the study. Therefore, it was concluded that foreign direct investment has long-run impact on economic growth. Likewise, VEC revealed that foreign direct investment, exchange rate and money supply cause real GDP in the short run. The results support the theoretical prediction that foreign direct investment would play an active role in economic growth as it positively leads to the GDP. The study, therefore, concludes that foreign direct investment is driving the economic growth in Sri Lanka.
 
 Keywords: Foreign Direct Investment, Economic Growth, Vector Error Correction Model, Sri Lanka

Return and volatility spillover between India and leading Asian and global equity markets: an empirical analysis

PurposeThe study uses the multivariate GARCH-BEKK model (which was first proposed by Baba et al. (1990) and then further developed by Engle and Kroner (1995)) to examine the return and volatility spillover between India and four leading Asian (namely, China, Japan, Singapore and Hong Kong) and two global (namely, the United Kingdom and the United States) equity markets.Design/methodology/approachThe study employs a multivariate GARCH-BEKK model to quantify return correlation and volatility transmission across the pre- and post-2008 global financial crisis periods (apart from other conventional time series modelling like cointegration, Granger causality using vector error correction model (VECM)).FindingsThe results show a tendency of the Indian stock market index to move along with the US and Hong Kong market indices. The decrease in the value of the co-integration coefficient during the recession was explained by reduced investor confidence in developing countries. The result further shows a clear distinction in terms of volatility spillover between the Asian market vis-a-vis US and UK markets. Volatility transmission from India to Asian markets was found to be significantly higher as compared to the US and UK. So also, the study’s results show a puzzling result giving us comparable co-integration ranks for phase 2 (expansion) and phase 3 (slow-down) of the business cycle in most cases.Research limitations/implicationsIn Granger causality testing, the results were unable to ascertain the difference between phase 2 (expansion) and phase 3 (slowdown). However, the multivariate GARCH (MGARCH)-BEKK model showed a clear reduction in volatility transmission to NIFTY50 (is the flagship index on the National Stock Exchange of India Ltd. (NSE)) as India entered slow-down. This shows that the Indian economy does go through different business cycles, and the changes in parameters hence prove hypothesis 3 to be true with respect to volatility transmission to India from International markets.Originality/valueThe results show that for all countries, the volatility transmitted to India increases significantly going from phase 1 (recession) to phase 2 (expansion) and reduces again once the countries enter slow-down in phase 3 (slowdown). This shows that during expansion shocks and impulses in international markets affect the Indian markets significantly, supporting the increase in co-integration in phase 2 (expansion). During expansion, developing markets like India become profitable for investors, due to the high growth rate when compared to developed countries. This implies that a significant amount of capital enters Indian markets, which is susceptible to the volatility of international markets. The volatility transmission from India to the US and UK was insignificant in phase 1 (recession and recovery) and phase 3 (slow-down) showing a weak linkage between the markets during volatile time periods.

Analysis of Some Energy and Economics Variables by Using VECMX Model in Indonesia

Time series modeling analysis is one of the methods to forecast based on past data and conditions. The analytical tool that is commonly used to forecast multivariate time series data is the Vector Autoregressive (VAR) model. However, when the variables have cointegration and stationary at the first difference value, then the VAR model is modified into the Vector Error Correction Model (VECM). In VECM, all variables can be used as endogenous variables. If exogenous variables are involved in the VECM model, then the model is called as Vector Error Correction Model with Exogenous variables (VECMX). In the present study, a time series modeling analysis was used to analyze the price of gasoline, the money supply in a broad sense (M2), oil and gas exports, and consumption imports over the years from 2012 to 2020. By using information on the criteria of Akaike Information Criterion Corrected, Hannan–Quinn Criterion, Akaike Information Criterion, and Schwarz Bayesian Criterion, the best VAR(p) model is obtained with order 3, or lag 3. Based on the VAR(3) model, the cointegration test is conducted, and the result shows that there is a long-term relationship among variables, namely, there is a cointegration relationship between variables with rank = 1. Based on the cointegration rank = 1 and the smallest value of the information criteria and comparison of some candidate best models, namely, VECMX(2,1), VECMX(2,2), VECMX(3,1), VECMX(3,2), and VECMX(4,1), we found that the best model is VECMX(3,1) with lag 3 for endogenous variables and lag 1 for exogenous variables. Based on this best model, further analysis of Granger causality, Impulse Response Function (IRF), and forecasting is discussed.

Johansen‐type cointegration tests with a Fourier function

This article extends the pioneering Johansen cointegration test to allow for structural breaks in a cointegration system. Instead of using usual dummy variables, we utilize a Fourier function to control for an unknown number of multiple breaks in the cointegration system. The underlying presumption of the procedure is that structural breaks often can be captured by using a small number of low‐frequency components from a Fourier approximation. The number of parameters to estimate is reduced significantly, which can lead to a good performance of the tests. Monte Carlo simulations show that the new tests display good size and power properties, except for the cases of sharp breaks. Then, we consider a strategy using a union of rejections. The union test combines our suggested test with a test of the cointegration rank in VAR models in the presence of a possible break in trend at an unknown point. We further consider a procedure that selects a better model using a Schwarz‐type criterion among Johansen, trend break‐point, and Fourier models. The resulting test shows fairly correct sizes in all cases, including sharp breaks, smooth breaks, and no breaks. The power properties are also reasonable in almost all cases.

Inflation, Unemployment and Labor Force Change in Indonesia: What Does the Connection?

The issue of relationship between inflation and unemployment is one of the topics which have been discussed for long time. Philips Theory says that inflation rate has a relationship to unemployment rate, it becomes very interesting to observe the data of Indonesian Phenomena refer to the above theory therefore, this objective of this paper is to narrow the gap in literature by examining the long-run relationship between the change of labor force level, LF (t), inflation, ? (t), unemployment, UE (t), in Indonesia. It also to investigate the individual relationship between the change rate of LF and inflation, and change rate of LF and unemployment. Therefore, we use two different methods to test the cointegration. First is the Engle Granger approach based on the unit root test in the residuals of linear regression, which also includes a number of specification tests, Second method is the Johansen cointegration rank test based on a VAR representation, which is also proved to be an adequate one via a set of appropriate tests. This study used vector time series analysis to analyze the linear lag relationship between inflation, unemployment rate and the change in labor force participation. Under the empirical framework, the study adopted Vector Auto Regression (VAR) model. Results of this research, It is obtained from the Pearson correlation coefficient (correlation Pearson coefficient =0.059, for a significance level at 12% higher than the 5% the chosen one), that between the two variables there is a direct negative relationship, but of a very low and statistically insignificant medium intensity. This fact tell us to state that in the long run (23 years) between inflation and unemployment in Indonesia there is no significant relation. On the other hand, we noticed that there is also direct significant relationship between inflation and labor change. The Pearson coefficient = 0.080 for a significant level; at 13.5% greater than 5% from the chosen one, Which means that only 9.5% of the change in labor force was influenced by inflation. This denotes a very low and statistically insignificant medium intensity.

Macroeconomic Variables and Gross Domestic Product: Evidence from Sri Lanka

The main objective of the study is to investigate the empirical relationship between macroeconomic variables and real gross domestic product (GDP) in Sri Lanka. Exchange rate, government spending, interest rate, money supply and unemployment rate were considered as selected macroeconomic variables. Real GDP was considered as a dependent variable. The current study used annual time series data over the period from 1990 to 2019 which were collected from the annual reports of the Central Bank of Sri Lanka. Stationary of the data was tested using the Augmented Dickey-Fuller test. Johansen co-integration rank test, max Eigen value test, Vector Error Correction along with Wald causality test were used to estimate the relationship between macroeconomic variables and GDP. At the 5% level of significance, the co-integration rank test and max Eigen value test revealed that there are four co-integration equations exist in this study. Therefore, it was concluded that selected macroeconomic variables have long-run impact on GDP. Likewise VEC and Wald test revealed that the all the selected macroeconomic variables causes GDP in the short run. The results support the theoretical prediction that macroeconomic variables would play an active role in GDP. The study, therefore, concludes that macroeconomic variables are driving GDP in Sri Lanka. Thus, growth-oriented macroeconomic policies should be established for protecting poor people in the country.

Model Identification Via Total Frobenius Norm of Multivariate Spectra

Abstract We study the integral of the Frobenius norm as a measure of the discrepancy between two multivariate spectra. Such a measure can be used to fit time series models, and ensures proximity between model and process at all frequencies of the spectral density—this is more demanding than Kullback–Leibler discrepancy, which is instead related to one-step ahead forecasting performance. We develop new asymptotic results for linear and quadratic functionals of the periodogram, and make two applications of the integrated Frobenius norm: (i) fitting time series models, and (ii) testing whether model residuals are white noise. Model fitting results are further specialized to the case of structural time series models, wherein co-integration rank testing is formally developed. Both applications are studied through simulation studies, as well as illustrations on inflation and construction data. The numerical results show that the proposed estimator can fit moderate- to large-dimensional structural time series in real time, an option that is lacking in current literature.

Determinants of Private Savings Effect on Economic Growth in Ethiopia

Private saving is a very important factor in bringing economic development, its working or efficiency is determined by different socio economic and political factors. In Ethiopia, private saving does not have a deep-rooted history because of frequent policy changes following the changes of government. The objective of this paper is to analyse the determinants of private saving in Ethiopia and also to check the long run or short run impact of real per capita GDP, real deposit interest rate, age dependency ratio, inflation rate and number of bank branches on private savings using time series annual data from 1978 to 2018. The research methodology employed are tests such as testing for stationery (unit root test) and co-integration test, rank of co-integration determined by using ARDL (Autoregressive- Distributed Lag) to characterize long-run and the short-run relationship between private saving and independent variables. The model is estimated by using Ordinary Least Square (OLS) and/or E-Views 10 also offered a specialized estimator for handling ARDL model. The estimated results revealed that real per capita GDP, real deposit interest rate, age dependency ratio and number of bank branches have found to be statistically significant and positive effect (but real per capita GDP negative in the short run) on private savings while inflation rate is found non-significant and negative effect on private savings in Ethiopia both in the long and short run periods in the study period. Based on the result, the researcher concluded that level of real per capita GDP and number of bank branches is found to be important variable and have very significant impact on private savings. Finally, the study recommended that the national level policy makers or decision makers has to take measure to improve income levels of society and special attention to increases financial access throughout the country by further expanding bank branches or other financial institutions and their services to increase private savings. Keywords : Determinants of private savings, Economic growth, ARDL, co-integration, Ethiopia DOI: 10.7176/JPID/60-01 Publication date: July 31 st 2021

Sustainability of Women’s Employment Rate for Malaysian Economic Development

This research paper develops a model for the sustainability of women’s employment rate in Malaysia’s economic development. This study examined annual data from 1982 to 2018, with 37 observations. A new econometric method was adopted to determine both short-run and long-run relationships among the variables using the Johansen Cointegration rank test, Vector Error Correction Method (VECM) with error correction model of cointegration equation. The VECM results revealed significant and positive short-term relationships between foreign direct investment, gross domestic product (GDP), and the negative short-term relationship of the lagged period of women’s employment rate to women employment rate (WER). The variables, GDP, education level, and women’s marital status are cointegrated and have a long-term relationship between WER in the cointegration equation. The Johansen Cointegration rank test also showed the existence of cointegration equations, and a long-term relationship between the variables. Eventually, the residual diagnosis, significant error term, and the performance of the model evaluation were found as satisfactory and valid. In short, this research paves the way for policymakers to construct a better policy for the future of women’s employment sustainability.

Inflation, Unemployment and Labor Force Change in Indonesia: What Does the Connection?

The issue of relationship between inflation and unemployment is one of the topics which have been discussed for long time. Philips Theory says that inflation rate has a relationship to unemployment rate, it becomes very interesting to observe the data of Indonesian Phenomena refer to the above theory therefore, this objective of this paper is to narrow the gap in literature by examining the long-run relationship between the change of labor force level, LF (t), inflation, ? (t), unemployment, UE (t), in Indonesia. It also to investigate the individual relationship between the change rate of LF and inflation, and change rate of LF and unemployment. Therefore, we use two different methods to test the cointegration. First is the Engle Granger approach based on the unit root test in the residuals of linear regression, which also includes a number of specification tests, Second method is the Johansen cointegration rank test based on a VAR representation, which is also proved to be an adequate one via a set of appropriate tests. This study used vector time series analysis to analyze the linear lag relationship between inflation, unemployment rate and the change in labor force participation. Under the empirical framework, the study adopted Vector Auto Regression (VAR) model. Results of this research, It is obtained from the Pearson correlation coefficient (correlation Pearson coefficient =0.059, for a significance level at 12% higher than the 5% the chosen one), that between the two variables there is a direct negative relationship, but of a very low and statistically insignificant medium intensity. This fact tell us to state that in the long run (23 years) between inflation and unemployment in Indonesia there is no significant relation. On the other hand, we noticed that there is also direct significant relationship between inflation and labor change. The Pearson coefficient = 0.080 for a significant level; at 13.5% greater than 5% from the chosen one, Which means that only 9.5% of the change in labor force was influenced by inflation. This denotes a very low and statistically insignificant medium intensity