The relationship between inflation and unemployment in viet nam an ardl bounds testing approach

THAI NGUYEN UNIVERSITY UNIVERSITY OF AGRICULTURE AND FORESTRY JOHN HENRY LACAMPUEÑGA PAPA THE RELATIONSHIP BETWEEN INFLATION AND UNEMPLOYMENT IN VIET NAM: AN ARDL BOUNDS TESTING APPROACH BACHELOR THESIS Study Mode: Full-time Major: Agricultural Economics Faculty: Advanced Education Program Office Batch: 2018 – 2021 Thai Nguyen, 11/01/2022 Thai Nguyen University of Agriculture and Forestry Degree Program Student name Student ID Thesis Title Bachelor of Agricultural Economics John Henry Lacampueñga Papa DTN1854250005 The Relationship Between Inflation and Unemployment in Viet Nam: An ARDL Bounds Testing Approach Supervisor (s) Dr Nguyen Thi Lan Anh Supervisor’s Signature Abstract: Inflation and unemployment are two of the most serious economic issues In order to establish the necessary policies to combat these issues, it is vital to comprehend their relationship The main objective of this study is to investigate the relationship between inflation and unemployment in Viet Nam The researcher employed the Autoregressive Distributed Lag (ARDL) model as a methodological framework for determining the co-integration relationship between the variables The period of observation was from year 1991 to year 2020 Annual data for inflation and unemployment were gathered for this study Using the ARDL Model, the researcher was able to identify a co-integration relationship between the two variable when inflation is considered as the dependent variable Moreover, the estimation also showed the negative and insignificant of the relationship both in the short-run and in the long-run Keywords: Inflation, Unemployment, ARDL Model, Viet Nam Number of pages: 49 Pages Date of Submission: 11/01/2022 ACKNOWLEDGEMENT This work would not have been possible without the presence, efforts, support, and prayers of my family and good friends, who motivated me to think and finish this research First and foremost, I would like to thank God for showering His blessings on me throughout this research, for allowing me to successfully complete the research, and for letting me get through all the difficulties I have experienced your guidance day by day Thank you for listening to all my prayers and for guiding me throughout this journey I would like to express my deepest gratitude to my family (Mr Telesforo C Papa II, Mrs Rocel L Papa, and Gabriel Oliver L Papa) for the sacrifices that they have made for educating me and for preparing me for my future I am forever grateful for the love, support, and understanding that you’ve given me throughout my college life You all served as my motivation to finish this thesis I would like to acknowledge and give my warmest thanks to my supervisor (Dr Nguyen Lan Anh) who made this work possible Your guidance and advice carried me through all the stages of writing this thesis I would like give thanks to my girlfriend (Angelica Millete S Adriano) who helped me a lot in this thesis Thank you for all the efforts that you have exerted and for staying up all night with me to finish my thesis All our hard work and efforts will pay off soon I would like to give thanks to my Elibap for being my stress reliever and for giving me a reason to be happy every day I would also like to thank all my friends (James, Raphael, Isaiah, JC, Ðức, Ronnieca, Hanna, Elisha, Jemimah, and Stefanie) for making my life here in Vietnam much easier and for being a family to me Thank you all for the love, care, and support that you’ve given me For all the people who believed in me, who stayed by my side, who I shared memorable moments with, and who taught me valuable lessons in life, a big thanks to all of you John Henry Lacampueñga Papa TABLE OF CONTENT LIST OF FIGURES LIST OF TABLES LIST OF ABBREVIATIONS PART INTRODUCTION 10 1.1 Research Rationale 10 1.2 Research Objective 11 1.3 Research Questions and Hypothesis 11 1.4 Limitations 12 1.5 Definition 12 PART II LITERATURE REVIEW 14 2.1 Inflation 14 2.2 Unemployment 19 2.3 Relationship Between Inflation and Unemployment 20 PART III METHODS 25 3.1 Data 25 3.2 Model Specification 25 3.3 Pre-estimation Test 27 3.3.1 Augmented Dickey Fuller Test 27 3.3.2 Optimal Lag Length Determination 28 3.4 Co-integration Test 28 3.5 Diagnostics 28 3.5.1 Autocorrelation Test 28 3.5.2 Heteroscedasticity Test 29 3.5.3 Normality Test 29 3.5.4 Parameter Stability Test 29 PART IV RESULTS 30 4.1 Graphical Presentation 30 4.2 Optimal lag length Selection 30 4.3 Stationarity Test Using Augmented Dickey Fuller Unit Root Test 31 4.4 ARDL Estimation Result 32 4.5 ARDL Bounds Test 35 4.6 Error Correction Model 36 4.7 Autocorrelation Test (Breusch-Godfrey LM Test) 37 4.8 Heteroscedasticity Test 38 4.9 Normality Test for Residuals 38 4.10 Stability Test 39 PART V DISCUSSION AND CONCLUSION 41 5.1 Discussion 41 5.2 Conclusion 42 REFERENCES 43 APPENDIX 49 LIST OF FIGURES Figure CPI Composition as of 2008 Figure Philips Curve Figuer Graphical Presentation of the Inflation and Unemployment Figure Cumulative Sum (CUSUM) Stability Test LIST OF TABLES Table Optimal Lag Length Selection Table Augmented Dickey Fuller (ADF) Unit Root Test Table Autoregressive Distributed Lag (ARDL) Model (1991-2020) Table ARDL Bounds Test Result Table Error Correction Model Table Breusch-Godfrey Serial Correlation LM Test Table Breusch-Pagan Test for Heteroscedasticity Table Jarque-Bera Normality Test LIST OF ABBREVIATIONS ARDL – Autoregressive Distributed Lag Model AIC – Akaike Information Criterion ADF – Augmented Dickey Fuller CUSUM – Cumulative Sum F Statistics 9.30 Prob(F Statistics) 0.0003 Source: Stata 13 Analysis 4.5 ARDL Bounds Test To evaluate if there is co-integration among the variables, as shown in table 3, the ARDL Bound test for Co-integration examines the F-statistic value and compares it to the upper and lower critical bound values If the F-statistic value exceeds the critical upper bound, the null hypothesis claiming a long-run relationship between the variables will be rejected If the F-statistic value is less than the critical lower bound, implying that there is no long-run association between the variables, the null hypothesis cannot be rejected If the F-statistics value falls between the lower and upper critical bounds, no strong implications about co-integration can be drawn The F statistic value of the equation INF=f(UNE) in this study is greater than the upper critical bound value at the 5% level of significance, indicating that there is a long-run relationship between the variables However, the F statistic value of the equation UNE=f(INF) is less than all of the significance level Therefore, there is no long-run relationship between the variables Table ARDL Bounds Test Result Estimated equation INF=f(UNE) UNE=f(INF) F-Statistics 6.449 3.371 Optimal Lag Length (1,1) (1,1) 35 Asymptotic Critical Bounds Lower bound I(0) Upper Bound I(I) 1% 6.84 7.84 5% 4.94 5.73 10% 4.04 4.78 Source: Stata 13 Analysis 4.6 Error Correction Model A co-integration relationship was found between inflation and unemployment when inflation is considered as the dependent variable Thus, error correction model should be used Table shows the conducted error correction model Table Error Correction Model LnINF Coefficient Std Err t P>|t| 95% confidence interval -.5326325 1514294 -3.52 0.002 -.8445071 -.2207579 -.6089049 1.078396 -0.56 0.577 -2.829904 1.612094 ADJ LnINF L1 LR LnUNE SR 36 LnUNE D1 -.6960788 _cons 1.210036 7178988 -0.97 0.342 -2.174619 7824616 5731124 2.11 0.045 0296892 2.390384 Source: Stata 13 Analysis 4.7 Autocorrelation Test (Breusch-Godfrey LM Test) As shown in table 6, the Breusch-Godfrey serial correlation LM Test reveals that there is no serial correlation in the model There was no serial correlation in the residuals as confirmed by the probability of Chi Table Breusch-Godfrey Serial Correlation LM Test !"#$ = % !&#' HO: No Serial Correlation Lags Chi2 df Prob > chi2 0.163 0.6861 !&#' = % !"#$ HO: No Serial Correlation Lags Chi2 df Prob > chi2 0.938 0.3329 37 Source: Stata 13 Analysis 4.8 Heteroscedasticity Test As shown in table 7, the Breusch-Pagan Test reveals that there is no heteroscedasticity in the model There was no heteroscedasticity as confirmed by the probability of Chi Table Breusch-Pagan Test for Heteroscedasticity !"#$ = % !&#' HO: Constant Variance Chi2(1) 0.12 Prob > chi2 0.7331 !&#' = % !"#$ HO: Constant Variance Chi2(1) 0.65 Prob > chi2 0.4203 Source: Stata 13 Analysis 4.9 Normality Test for Residuals As shown in table 8, the Jarque-Bera Test reveals that the residuals of the equation LnINF=f(LnUNE) is not normally distributed However, the residuals of the equation LnUNE=f(LnINF) are normally distributed 38 Table Jarque-Bera Normality Test !"#$ = % !&#' HO: Normality Jarque-Bera 155.9 Chi2 1.4e-34 !&#' = % !"#$ HO: Normality Jarque-Bera 3.379 Chi2 1846 Source: Stata 13 Analysis 4.10 Stability Test Figure below shows the graph of Cumulative Sum (CUSUM) Stability Test of the two equations from the year 1991-2020 Both graphs show instability at a certain point of time The outcome is unfavorable since the study's sample period was not steady throughout 39 !"#$ = % !&#' !&#' = % !"#$ Source: Stata 13 Analysis Figure Cumulative Sum (CUSUM) Stability Test 40 PART V DISCUSSION AND CONCLUSION 5.1 Discussion This study hypothesized that the inflation and unemployment in Vietnam has a cointegration relationship Autoregressive Distributed Lag (ARDL) Bound Test was used to determine if a co-integration exists between the two variable The result shows that there is co-integration relationship between inflation and unemployment in Vietnam when inflation is considered as the dependent variable The F Statistics of 6.449 which is higher than the upper critical bound I (1) of 5.73 at 5% level of significance proves that co-integration exists Thus, a long-run relationship between the variables also exists In this case, the null hypothesis of no co-integration between the variables is rejected An error correction model was conducted for the co-integrated variables The adjustment coefficient of -.5326325 with a p-value of 0.002 shows a statistical significance This means that the speed of adjustment is 53.3 % compared to the equilibrium path This implies that any future deviation from the equilibrium level of inflation during the current period will be reduced by 53.3 % in the next period of time The result also suggests that a 1% increase in the unemployment rate reduces the inflation rate by 0.61% in the long-run According to the ARDL estimation result, it shows that inflation and unemployment has insignificant relationship both in the short-run and in the long-run A p-value of 0.168 and which is higher than 0.05 indicates the insignificance of the relationship of the two variables in the short-run Likewise, a p-value of 0.577 also indicates the insignificance of the relationship in the long-run 41 5.2 Conclusion The purpose of this study was to examine the relationship between inflation (INF) and unemployment (UNE) in Vietnam with annual data from the period 1991–2020 (30 years) To achieve the objective of this study, the two variables was analyzed using an Autoregressive Distributed Lag (ARDL) Model Based on the results, the coefficient of unemployment showed a negative and insignificant impact on inflation in the short-run Similar with the coefficient of inflations which also showed a negative and insignificant impact on unemployment in the short-run Moreover, it was found that there exists a cointegration relationship between the variables when inflation is considered as the dependent variable (LnINF=f(LnUNE)) at 5% level of significance Thus, it was concluded that there exist a long-run relationship between the variables In addition, the coefficient of unemployment showed a negative and insignificant impact on inflation on the long-run According to the findings of the study, the relationship of inflation and unemployment should be addressed while creating policies in Vietnam in order to maintain price stability and reduce unemployment Long-term plans should include preventative measures to manage both inflation and unemployment, as well as required structural adjustments As additional data becomes accessible, future researchers may consider employing ARDL modeling with quarterly or monthly data 42 REFERENCES Altay, B., Tucu, C.T., Topỗu, M (2011) sizlik ve enflasyon oranları arasındaki nedensellik ilişkisi: G8 ülkeleri örneği Afyon Kocatepe Üniversitesi İİBF Dergisi, 8(2), 1-26 Bayrak, M., Kanca, O.C (2013) Türkiye’de Phillips eğrisi üzerine bir uygulama Eskişehir Osmangazi Üniversitesi İİBF Dergisi, 8(3), 97-115 Bernanke, B S., Laubach, T., Mishkin, F S., & Posen, A S (2018) Inflation Targeting: Lessons from the International Experience Princeton University Press Bhattacharya, R (2014) Inflation dynamics and monetary policy transmission in Vietnam and emerging Asia Journal of Asian Economics, 34, 16–26 Bhattarai, K (2016) Unemployment–inflation trade-offs in OECD countries Economic modelling, 58, 93-103 Büyükakın, T (2008) Phillips eğrisi: Yarım yüzyıldır bitmeyen tartışma İ.Ü Siyasal Bilgiler Fakültesi Dergisi, 39, 133-159 Cagan, P (1956) The Monetary Dynamics of Hyperinflation In M Friedman, Studies in the Quantity Theory of Money Chicago: University of Chicago Press Camen, U., 2006, “Monetary Policy in Vietnam: The case of a transition country” in “Monetary Policy in Asia: approaches and implementation”, BIS Papers, Vol 31, pp 232- 252, Bank for International Settlements, Basle, Switzerland 43 Carvalho, d., Ribeiro, & Marques (2017) Economic decelopment and infaltion: a theoretical and empirical analysis International Review of Applied Economics, 546 - 565 Chappelow, J (2020) Guide to Unemployment Retrieved https://www.investopedia.com/terms/u/unemploymentrate.asp from: (accessed on 12/23/2021) Chowdhury, A (2008) Methods explained: the GDP implied deflator Economic & Labour Market Review, 53 - 56 Di Tella, R., MacCulloch, R J., & Oswald, A J (2001) Preferences over inflation and unemployment: Evidence from surveys of happiness American economic review, 91(1), 335-341 Duasa, J & Ahmad, N (2009) Identifying good inflation forecaster MPRA Paper No 13302 Retrieved from http://mpra.ub.uni-muenchen.de/13302/ Fernando, J (2020) Inflation [Online] Available at https://www.investopedia.com/terms/i/inflation.asp (Accessesd: 18 November 2020) Fischer, S., & Modigliani, F (1978) Towards and Understanding of the Real Effects of the Costs of Inflation NBER Working Papers Fischer, S., Sahay, R., & Vegh, C A (2002) Modern Hyper- and High Inflations NBER Working Papers 44 Fisher, I (1933) The Debt-Deflation theory of Great Depressions Econometrica, 337 357 Friedman, M (1977) Inflation and unemployment The Journal of Political Economy, 85(3), 451-472 Furuoka, F (2007) Does the Phillips curve really exist? New empirical evidence from Malaysia Economics Bulletin, 5(16), 1-14 Geronikolau, G., Spyromitros, E., & Tsintzos, P (2020) Progressive taxation and human capial as determinants of inflation persistence Economic Modelling, 82 97 Gujarati, D N (2004) Basic Econometrics 4th Edition The McGraw-Hill Companies 2004 Hall, T.E., Hart W.R (2012) The samuelson-solow "Phillips Curve" and the great inflation History of Economics Review, 62-72 Hayes, A (2021) What is Unemployment? [Online] https://www.investopedia.com/terms/u/unemployment.asp Available (Accessed: at 23 February 2021) Holt, C C (1971) The Unemployment-Inflation Dilemma: A Manpower Solution ILO, IMF, Eurostat, UN, OECD, & WorldBank (2020) Consumer Price Index Manual IMF Library 45 ILO, IMF, OECD, UNECE, & WorldBank (2004) Producer Price Index Manual IMF Library Jahoda, M (1982) Employment and unemployment: A social-psycho logical analysis Cambridge: Cambridge University Press Kohli, U (2004) Real GDP, real domestic income, and terms-of-trade changes Journal of International Economics, 83 - 106 Kripfganz, S., & Schneider, D C (2018, September) ardl: Estimating autoregressive distributed lag and equilibrium correction models In Proceedings of the 2018 London Stata Conference Laidlier, D (2000) Highlights of The Bullionist Controversy Department of Economics, University of Western Ontario Lepetit, A (2020) Asymmetric unemployment fluctuations and monetary policy tradeoffs Review of Economic Dynamics, 36, 29-45 Liu, Z & Rudebusch, G (2010) Inflation: Mind the gap FRBSF Economic Letter 201002, January 19 Maliszewski, W S., 2010, “Vietnam: Bayesian Estimation of Output Gap”, IMF Working Paper 10/149, International Monetary Fund, Washington, D.C., U.S.A Mlatsheni, C., & Leibbrandt, M (2011) Youth unemployment in South Africa: challenges, concepts and opportunities Journal of International Relations and Development, 14(1), 118–126 46 Modigliani, F., Papademos, L (1975) Monetary policy for the coming quarters: The conflicting views The New England Review, 3, 2-35 Moulton, B R., & Moses, K E (1997) Addressing the Quality Change Issue in the Consumer Price Index Brookings Papers on Economic Activity, 305 - 366 Mulok, D., Asid, R., Kogid, M., & Lily, J (2011) Economic growth and population growth: Empirical testing using Malaysian data Interdisciplinary Journal of Research in Business, 1(15), 17-24 Ndzwayiba, Anga'Wandisa (2020) What Is Unemployment Nishizaki, K., Sekine, T., & Ueno, Y (2012) Chronic Deflation in Japan Bank of Japan Working Paper Series Pettinger, T (2019) Definition of Unemployment [Online] Available at https://www.economicshelp.org/blog/2247/unemployment/definition-ofunemployment/ (Accessed: 27 February 2019) Phillips, A.W (1958) The Relation between unemployment and the rate of change of money wage rates in the United Kingdom: 1861-1957 Economica, 25, 283-299 Puzon, K A M (2009) The inflation dynamics of the ASEAN-4: A case study of the Phillips curve relationship Marsland Press, Journal of American Science, 5(1), 55-57 Rodernburg, P (2007) Derived measurement in macroeconomics: Two approaches for measuring the NAIRU considered Tinbergen Institute Discussion Paper 017 47 Samuelson, P A., Solow, R.M (1960) Problem of achieving and maintaining a stable price level: Analytical aspects of anti-inflation policy American Economic Review, 50(2), 177-194 Shrestha, B and Bhatta G R (2018) Selecting appropriate methodological framework for timeseries data analysis The Journal of Finance and Data science, 4(2): 7189 Uysal, D., Erdoğan, S (2003) Enflasyon ile işsizlik oranı arasındaki ilişki ve Türkiye örneği (1980-2002) SU İİBF Sosyal ve Ekonomik Araştırmalar Dergisi, 6, 3547 Vaughan, R (1675) A Discourse of Coin and Coinage London: Th Dawks Van Aardt, 2009 Labour policy and job creation: Too many holy cows? In Parsons, R (Ed.), Zumanomics 1st edn Jacana Media (Pty) Ltd, Auckland, 129 –48 Wai, U T (1959) The Relation Between Inflation and Economic Development Staff Papers: International Monetary Fund, 302 - 317 World Bank, 2012, “Taking Stock: An Update on Vietnam’s Recent Economic Developments”, December, The World Bank, Washington, D.C., U.S.A Yıldırım, K., Karaman, D (2003) Makroekonomi Eskişehir: Eğitim Sağlık ve Bilimsel Araştırmalar Vakfı Yay 48 APPENDIX Annual data on Unemployment (UNE) and Inflation (INF) are retreived from the website of World Bank and are presented in the table below The data are both transformed into their logarithmic form (LnUNE and LnINF) A total of 30 observations from year 1991 to year 2020 were used in this study Year UNE INF inf1 LnUNE LnINF 1991 1.83 81.8 83.8 0.604316 4.428433 1992 1.86 37.7 39.7 0.620577 3.681351 1993 1.91 8.4 10.4 0.647103 2.341806 1994 1.93 9.5 11.5 0.65752 2.442347 1995 1.93 16.9 18.9 0.65752 2.939162 1996 1.93 5.675 7.675 0.65752 2.037968 1997 2.87 3.21 5.21 1.054312 1.65058 1998 2.29 7.266 9.266 0.828552 2.226352 1999 2.33 4.117 6.117 0.845868 1.811072 2000 2.26 -1.71 0.29 0.815365 -1.23788 2001 2.76 -0.432 1.568 1.015231 0.449801 2002 2.12 3.831 5.831 0.751416 1.763189 2003 2.25 3.235 5.235 0.81093 1.655367 2004 2.14 7.755 9.755 0.760806 2.27778 2005 2.14 8.285 10.285 0.760806 2.330687 2006 2.08 7.418 9.418 0.732368 2.242623 2007 2.03 8.344 10.344 0.708036 2.336407 2008 1.79 23.115 25.115 0.582216 3.223465 2009 1.74 6.717 8.717 0.553885 2.165275 2010 1.11 9.207 11.207 0.10436 2.416538 2011 18.678 20.678 3.02907 2012 1.03 9.095 11.095 0.029559 2.406495 2013 1.32 6.593 8.593 0.277632 2.150948 2014 1.26 4.085 6.085 0.231112 1.805827 2015 1.85 0.631 2.631 0.615186 0.967364 2016 1.85 2.668 4.668 0.615186 1.540731 2017 1.87 3.52 5.52 0.625938 1.708378 2018 1.16 3.54 5.54 0.14842 1.711995 2019 2.04 2.796 4.796 0.71295 1.567782 2020 2.27 3.221 5.221 0.81978 1.652689 49