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.. Monetary policym
INTRODUCTION
Research Rationale
Inflation and unemployment are critical economic challenges that require strategic attention Due to their inverse relationship, it is impossible for countries to simultaneously eradicate both unemployment and inflation.
In macroeconomics, the Phillips Curve concept investigates this inverse relationship
Inflation refers to the reduction in the purchasing power of a currency over time, evidenced by a rise in the general price level, indicating that a currency can buy less than it could in the past (Fernando, 2020) This phenomenon is a universal occurrence.
It is also a significant predictor of well-being (Tella et al, 2001; Duasa & Nursilah,
One of the major problems concerning inflation is that when it gets higher, it causes a regressive effect on lower-income households who may be working on a fixed income
If the price of goods and services rise higher than wages, there would be a sharp reduction in real earnings
Compared with the previous year, Vietnam recoded a 2.8% average inflation rate in
2019 Inflation in Vietnam appears to have stabilized after a stunning dip below 1% in
2015, and is expected to settle at approximately 4% in the coming years
Unemployment occurs when an individual of working age is eager and willing to work full-time but is unable to secure suitable employment opportunities This situation highlights the challenges faced by those actively seeking work yet struggling to find decent jobs (Pettinger, 2019).
With more unemployed workers, overall economic output would be smaller than it would be otherwise (Hayes, 2021)
According to General Statistics Office of Vietnam, the unemployment in Vietnam dropped from 2.50 percent in the third quarter of 2020 to 2.37 percent in the fourth quarter of 2020
Monetary policymakers have long debated the relationship between inflation and unemployment, which relates inflation to economic gap metrics like unemployment (Liu
The relationship between unemployment and inflation is a key consideration in monetary policy, as highlighted by economists like Liu and Rudebusch (2010) This trade-off presents challenges, as addressing one often comes at the cost of the other, complicating efforts to tackle pressing domestic issues such as poverty, crime, and pollution (Holt et al., 1971).
Research Objective
General Objectives: The objective of this study is to investigate any existent relationship between unemployment and inflation in Vietnam
• To identify if inflation and unemployment are co-integrated
• To identify if inflation and unemployment has a significant relationship.
Research Questions and Hypothesis
Is there a significant relationship between inflation and unemployment in Vietnam?
H o – There is no co-integration relationship between inflation and unemployment in Vietnam
H a - There is a co-integration relationship between inflation and unemployment in Vietnam
Limitations
This study analyzes data from 1991 to 2020, highlighting the limitation of data availability Due to the unavailability of monthly and quarterly data, annual figures for inflation and unemployment were utilized The primary objective is to determine the existence of co-integration and to assess the significant relationship between inflation and unemployment in Vietnam.
Definition
Inflation - an increase in prices and a decrease in the purchasing power of money
Inflation Rate - the rate at which a currency's value declines and, as a result, the general level of prices for goods and services rises
Unemployment – occurs when people are out of job and actively looking for work
Unemployment Rate - the percentage of the workforce that is unemployed
Time Series Data Analysis - a method of studying a collection of data points over a period of time
Co-integration Test - a test used to determine if a long-term correlation is present between many time series
Unit Root Test - a test for stationarity in a time series It determines whether the time series data is stationary or non-stationary
LITERATURE REVIEW
Inflation
Inflation reflects the changes in the overall price level within an economy, significantly influencing asset values by shaping market participants' expectations Often referred to as “the bane of central bankers” (Bernanke), inflation plays a crucial role in economic outcomes.
In 2002, it was highlighted that while structural variables such as the rule of law, organizational strength, environment and infrastructure, taxation, efficacy, incentive structures, and the welfare state play crucial roles, inflation remains a key focus of cyclical policy.
Deflation and hyperinflation are two types of inflation that can lead to severe economic consequences Deflation, often resulting from a decline in total demand, can make recovery challenging, especially during periods of debt deflation when prices and economic activity plummet, increasing actual debt burdens (Fisher, 1933; Bernanke, 2002) Conversely, hyperinflation is characterized by extreme money creation to support government spending, typically exceeding 50% inflation (Cagan, 1956) During hyperinflation, paper assets lose value rapidly, prompting governments to issue larger denominations of banknotes Cagan (1956) identifies two main drivers of hyperinflation: the monetization of shortages and fluctuating inflation expectations among individuals, which create a momentum effect.
Shifting from a time of predictable and steady inflation rate to becoming unpredictable which generates uncertainty in the economy and may erode trust in nominal assets In
15 economies that aren't designed to deal with high and unpredictable inflation, this uncertainty contributes to poor economic performance (Fischer et Al., 2002), (Cagan,
1956), (Fischer & Modigliani, 1978) It is extremely difficult for countries to avoid times of high and fluctuating inflation
It is indeed a complex task to appoint indices and there are various ways to intricately measure inflation Here are some of the most used ways to measure inflation:
The Consumer Price Index (CPI) measures changes in the prices of goods and services bought by consumers (ILO, et al., 2020) It is one of the most widely used indicators of inflation, although the methods for calculating CPIs differ from one country to another.
Recalling the criticisms of the Consumer Price Index (CPI) over the years is crucial, as it not only tracks product price changes but also accounts for shifts in living costs and consumer diversity According to Moulton & Moses (1997), the CPI in the United States is often inaccurate by more than 1% annually, largely due to its failure to adequately reflect improvements in product quality and evolving consumer preferences in response to price fluctuations.
Figure 1 CPI Composition as of 2008
The producer's rate of change in the prices of products and services purchased and sold is measured by producer price indices (ILO, IMF, OECD, UNECE & World Bank,
The Producer Price Index (PPI) is a collection of pricing indices based on principles established by organizations such as the ILO, IMF, OECD, UNECE, and World Bank Notably, the PPI concept predates the Wholesale Price Index, which measures changes in wholesale goods prices While the United States transitioned from the Wholesale Price Index to the PPI in 1978, the former remains in use in countries like India and the Philippines.
Conventional wisdom suggests that fluctuations in the Producer Price Index (PPI) often predict changes in the Consumer Price Index (CPI), as increased costs are eventually passed on to consumers Despite extensive research on the relationship between PPI and CPI, a broad consensus on this conversion remains elusive.
17 whether the two have a one-way causal link When looking into the reasons of inflation, we go over the literature on the subject
GDP deflators represent a unique measure of inflation, defined as the ratio of nominal GDP to real GDP Unlike other inflation metrics, GDP deflators do not rely on a fixed basket of goods and services However, they may still encounter similar challenges, such as the influence of improved terms of trade on price phenomena (Kohli, 2004).
Identifying the roots of inflation is as old as the practice of estimating inflation Vaughan
In 1675, efforts were made to distinguish between inflation caused by currency depreciation and that resulting from gold inflow This differentiation between cost-push and demand-driven inflation has its roots in the late 18th century's 'Bullionist Controversy' (Laidlier, 2000).
(1959) made another distinction, in which he separates inflation that is driven by investments from inflation that is driven by consumer and proclaims to have less danger and long-lasting
Anticipating inflation, whether through voluntary measures or built-in inflation-adjustment mechanisms, is recognized as a contributing factor to inflation (Carvalho, et al., 2017) For instance, falling inflation expectations have been identified as a cause of deflation in Japan (Nishizaki, et al., 2012) In Israel, to mitigate the worsening of near-hyperinflation, automated wage increases had to be suspended This highlights the importance of assessing inflation inertia in the Eurozone to effectively adjust monetary policy.
18 accordingly, the ECB established an inflation persistence network (Geronikolau, et al.,
Since the economic reforms of 1986, Vietnam has shifted from a centrally planned economy to a "socialist-oriented market economy." The liberalization policies introduced in 1990 led to a surge in exports and remarkable economic growth, with an average real GDP growth rate of 9% per year However, by 2012, this growth had slowed to 5%, influenced by stricter monetary and fiscal policies as well as the impacts of the global economic crisis (World Bank).
2012) Concurrently, inflation declined substantially in the year 2012, with inflation dropping down from 18.1% at the end of the year 2011 to 6.8% by the end of the year (Bhattacharya, 2014)
In the late 1980s, Vietnam experienced hyperinflation, with annual rates nearing 300% between 1986 and 1988, which decreased to below 20% by 1992 due to strict monetary and fiscal policies Although inflation remained low in the late 1990s and early 2000s, the country faced a decline in GDP, attributed to surplus capacity and low commodity prices, leading to two years of mild deflation from 2000 to 2001 By late 1999, the economy began to recover, albeit at a slower rate compared to the early 1990s.
Unemployment
Unemployment is a significant contemporary issue, as highlighted by Jahoda (1982) Ndzwayiba (2020) defines an unemployed individual as someone of working age who is capable, willing, and actively seeking employment Similarly, The Lumen Learning Course (2005) describes unemployment as "joblessness," emphasizing that those who are unemployed are actively pursuing job opportunities.
Unemployment, defined as the inability of individuals actively seeking work to find employment, serves as a crucial indicator of economic health (Chappelow, 2020) Mlatsheni and Leibbrandt (2011) highlight that the high rates of unemployment and worklessness significantly contribute to widespread social marginalization.
Unemployment serves as a vital economic indicator, highlighting the ability of individuals to secure employment and contribute to the economy's productivity (Chappelow, 2020) This trend may be influenced by the global crisis's effects on output growth and job availability, shifts in production structures, and the decreasing marginal utility of labor due to cost constraints, as noted by Van Aardt (2012).
Not all reasons for joblessness equate to unemployment According to the Bureau of Labor Statistics (2020), individuals who cease their job search are not counted in the unemployment rate, as they are no longer actively seeking employment.
Individuals who retire, return to school, or leave their jobs to care for family members are not classified as unemployed by the Bureau of Labor Statistics (BLS), even if they wish to work To be considered unemployed, one must have actively sought employment in the past month Those who have searched for work within the last year but not in the previous month are categorized as marginally unemployed This distinction contributes to what the BLS refers to as the "real unemployment rate."
Relationship Between Inflation and Unemployment
Numerous studies have explored the theoretical relationship between inflation and unemployment Philips (1958) established that the connection between changes in the unemployment rate and monetary earnings is non-linear, reversed, and stable Building on this concept, Büyükakın (2008) noted that monetary earnings increase more rapidly as unemployment decreases and rise more slowly as unemployment increases.
Samuelson and Solow (1960) revised the original Phillips curve to illustrate the relationship between wages and unemployment, shifting the focus from the connection between unemployment and the rate of change in nominal wages Instead, they examined the correlation between inflation and unemployment from 1934 to 1958 Hall and Hart (2012) note that the statistical Phillips curve is utilized to analyze the framework representing different inflation and unemployment scenarios.
The stability of the relationship between inflation and unemployment, as depicted by the Phillips curve, has been increasingly questioned, particularly regarding its long-term validity Yıldırım and Karaman (2003) argue that incorporating inflationary expectations suggests the Phillips curve is not stable over time, as selecting a point on the curve influences expected inflation rates and shifts the curve itself This analysis was further refined by other economists to address discrepancies between short-term and long-term expectations (Uysal & Erdoğan, 2003).
Friedman (1977) examined the distinct short-term and long-term impacts of inflation and unemployment, asserting that the Phillips curve accurately represents the short-term relationship but lacks a trade-off in the long run Altay et al (2011) support this view, indicating that the Phillips curve aligns parallel to the horizontal axis at the natural unemployment rate in the long term, suggesting that unemployment will stabilize at this natural rate regardless of inflation levels This concept aligns with Friedman's idea of the Natural Rate of Unemployment (NRU) as it relates to the Phillips Curve, highlighting the absence of a long-term trade-off.
Phelps and Friedman suggest a relationship between unemployment and inflation; however, this connection does not hold in the long run According to Rodenburg (2007), the natural unemployment rate is ultimately determined by real factors over an extended period.
In the 1980s, New Keynesian economists shifted from Friedman's Unemployment Rate to the Non-Accelerating Rate of Unemployment (NAIRU), a concept closely related to the Non-Inflationary Rate of Unemployment (NRU) initially defined by Modigliani and Papademos in 1975 and later refined by Tobin in 1980 NAIRU represents a stable unemployment rate that does not trigger inflation (ệzkửk & Polat, 2017) Both Monetarist and New Keynesian perspectives agree on the existence and slope of the Phillips curve; however, their interpretations differ significantly Monetarists attribute the long-term disappearance of the Phillips relationship to the correction of expectation errors, while Keynesians emphasize the role of flexible wages and prices (Bayrak and Kanca).
Many economists assert that the relationship between unemployment and inflation is crucial for monetary policy (Liu & Rudebusch, 2010) Central banks typically implement strategies to maintain low inflation, which may require high unemployment if an inverse relationship exists between the two (Asid et al, 2011) Consequently, this creates a trade-off between high inflation and low unemployment, or vice versa (Furuoka, 2007).
Research has extensively explored the relationship between unemployment and inflation, focusing on trade-offs, long-run dynamics, co-integration, and causality Bhattarai (2016) analyzed OECD countries, revealing significant trade-offs between unemployment and inflation, with varying unemployment rates and stabilized inflation due to targeted policies over the past two decades Utilizing quarterly data on inflation, unemployment, and growth rates, the study employed co-integration and Granger Causality Analysis, confirming a significant co-integrating relationship between the two variables This research will similarly apply co-integration and causality tests, specifically using the Autoregressive Distributed Lag (ARDL) bounds testing approach for co-integration and the Error Correction Model based on ARDL (ECM-ARDL) for causality analysis.
A study by Lepetit (2020) examined the trade-offs between unemployment fluctuations and monetary policy The findings revealed that when both constant errors and the elasticity of labor market tightness concerning labor productivity are high, a significant trade-off exists between stabilizing inflation and stabilizing unemployment.
Similarly, from 1980 to 2005, Puzon (2009) conducted a study in 4 ASEAN countries, namely: Thailand, Philippines, Malaysia, and Indonesia which examines the relationship
Researchers have examined the connections between inflation, unemployment, interest rates, exchange rates, and supply shocks Their findings indicate that there is no stable trade-off between unemployment and inflation, as demonstrated through various econometric methods, including ordinary least squares (OLS) and instrumental variables.
In Vietnam, there haven’t been research paper regarding the relationship between inflation and unemployment Therefore, the researcher will adapt similar studies regarding co-integration analysis in analyzing the data
METHODS
Data
This study examines the relationship between inflation and unemployment in Vietnam using time series data analyzed through the Autoregressive Distributed Lag (ARDL) Modeling Technique over a 30-year period from 1991 to 2020 The ARDL model, recognized for its effectiveness in evaluating economic variables in a single-equation time-series framework, has been widely utilized (Kripfganz & Schneider, 2016) Data on inflation and unemployment, sourced from the World Bank database, are presented as percentages Inflation is measured by the Consumer Price Index (CPI), reflecting the annual percentage change in the overall prices of a market basket of goods and services The unemployment rate is determined by the ratio of the unemployed active labor force willing to work to the total active labor force The analysis will be conducted using Stata version 13 statistical software.
Model Specification
The Autoregressive Distributed Lag Model (ARDL) is essential for making significant economic decisions based on historical data It captures the long-lasting effects of changes in economic variables on one another (Kripfganz and Schneider, 2018) The model incorporates both present and lagged values of the dependent variable as explanatory variables, utilizing endogenous and exogenous variables Prior to applying any testing methods in this analysis, it is crucial to conduct an initial test.
To ensure the validity of the ARDL model, it is crucial to assess the stationarity of the time series and determine the sequence of integration, confirming that no variable is integrated of order 2, or I(2) Only variables integrated of order I(0) and I(1) are eligible for this test The ARDL technique allows for a mix of integration orders, meaning that the variables in the system can be I(0), I(1), or a combination of both The structure of the ARDL model accommodates these variations effectively.
: Lag of Dependent Variable (LnINFt-1)
: Lag of Independent Variable (LnUNEt-1)
: Optimal lag length for dependent variable
: Optimal lag length for independent variable
Variables that are used to examine the relationship between Inflation and Unemployment in Vietnam are transformed into their logarithmic form (LnINF and
LnUNE) To minimize heteroscedasticity and provide direct elasticities in the datasets, the values of the time series are transformed into logarithm form (Obradovic et al.,
2017) The following models will be utilized in the analysis:
The linear relationship of these equations can be stated as: ln = + ln + (4) ln = + ln + (5)
In two separate equations, both \$\ln\$ terms serve as dependent variables, while the intercept term is denoted as \$\beta_0\$ The coefficient of the independent variable, which also includes both \$\ln\$ terms, is represented as \$\beta_1\$, and the error term is indicated as \$\epsilon\$.
Pre-estimation Test
Time series data must undergo a pre-estimation test to confirm that the model's assumptions are satisfied In this study, the Augmented Dickey-Fuller Unit Root test is employed to determine the stationarity of the variables.
The Augmented Dickey-Fuller Test (ADF) is a widely used method for testing the stationarity of time series data In time series analysis, the presence of unit roots can lead to misleading results This test helps determine whether a time series reverts to its long-run average value.
28 other aspects of the data series, such as variance and co-variance, are unaffected by changes in time, it is said to be stationary (Shrestha and Bhatta, 2018)
The Akaike Information Criterion (AIC), Schwartz Bayesian Criterion (SBC), and Hannan-Quinn Criterion (HQC) are effective tools for determining the optimal number of lags in model order selection.
In the case of this study, the Akaike Information Criterion (AIC) will be used to determine the optimal lag length.
Co-integration Test
The co-integration test follows the identification of the integration order through the ADF Unit Root Test, which assesses the long-run equilibrium relationship between multiple variables (Shrestha and Bhatta, 2018) The ARDL method utilizes two asymptotic critical bounds: the upper and lower bounds A F-statistic value that exceeds the upper bound leads to the rejection of the null hypothesis, indicating a long-run relationship among the variables Conversely, if the F-statistic is below the lower bound, the null hypothesis cannot be rejected, suggesting no long-run association exists When the F-statistic falls between the two bounds, no definitive conclusions about co-integration can be made.
Diagnostics
Autocorrelation refers to the extent of correlation between two subsequent time periods
In time series, it evaluates the relationship between the lagged version of a variable and
29 the original version In the case of this study, the Breusch-Godfrey LM Test will be used to check the existence of autocorrelation in the disturbance term
Heteroscedasticity in statistics refers to the situation where the standard deviations of a variable are not constant over time This study will utilize the Breusch-Pagan Test to assess the presence of heteroscedasticity in the disturbance term.
The Jarque-Bera (JB) test is utilized to assess the normality of residuals, with the null hypothesis positing that these residuals follow a normal distribution If the p-value is less than the chi-squared value, the hypothesis of normality can be rejected Conversely, a relatively large p-value, particularly when the statistic's value is near zero, indicates that the normality assumption cannot be dismissed (Gujarati, 2004).
The robustness of the estimated parameters in the regression model is essential for the post-estimation analysis of this study To identify any systematic or abrupt changes in the regression coefficients, the Cumulative Sum test is employed (Bhatti et al 2004).
RESULTS
Graphical Presentation
The graph illustrates the changes in individual variables over time, highlighting the fluctuations in specified macroeconomic factors It reveals whether the impact of these macroeconomic variables has intensified or diminished throughout the observation period Specifically, the graph below presents the trends of inflation and unemployment in Vietnam over a span of 30 years, from 1991 to the present.
Figure 3 Graphical Presentation of the Macroeconomic Variables (1991-2020)
Optimal lag length Selection
Determining the optimal lag length is crucial for ensuring the accuracy and quality of research findings, as both causality tests and F-statistics are sensitive to lag structure (Feridun and Shahbaz, 2010) Various criteria must be evaluated when establishing the ideal lag order, with one or two lags typically being sufficient.
Inflation in Vietnam (1991-2020) Unemployment in Vietnam (1991-2020)
To determine the optimal lag length for annual time series, the Akaike and Schwarz-Bayesian information criteria are essential tools (Jeffrey, 2012; Pesaran et al., 2001) The ideal lag length is identified by selecting the one with the lowest value In this study, the Akaike Information Criterion (AIC) indicated an optimal order of lags with a minimum value of 2.27043, as marked by an asterisk in Stata 13.
Table 1 Optimal Lag Length Selection
Stationarity Test Using Augmented Dickey Fuller Unit Root Test
Table 2 presents the results of the unit root test estimation using the Augmented Dickey-Fuller stationarity test at a 5 percent critical value The findings indicate that the variable LnINF is stationary at level, while the variable LnUNE is stationary at first difference.
Lag LL LR df p FPE AIC HQIC SBIC
Table 2 Augmented Dickey Fuller (ADF) Unit Root Test
ARDL Estimation Result
The ARDL model results, presented in Table 4, indicate that the unemployment variable (LnUNE) has a coefficient of -1.020401 and a p-value of 0.168, suggesting a negative and insignificant effect on inflation (LnINF) in Vietnam's short run Additionally, the adjusted R-Square reveals that 29.44% of the variation in the inflation rate is explained by the model.
Variables t-Statistics Critical Values t-Statistics Critical Values
33 variations in unemployment rate F-statistic value of 4.89 with p-value of 0.0082 indicates the ARDL model's significance and adequacy
In Vietnam, when analyzing unemployment as the dependent variable, the coefficient for inflation (LnINF) is -0.0730901 with a p-value of 0.168, suggesting a negative and statistically insignificant effect of inflation on unemployment (LnUNE) in the short run The adjusted R-squared value reveals that 47.08% of the variation in the inflation rate can be explained by changes in the unemployment rate Additionally, the F-statistic of 9.30 with a p-value of 0.0003 confirms the significance and adequacy of the ARDL model used in this analysis.
Table 3 Autoregressive Distributed Lag (ARDL) Model (1991-2020)
LnINF Coefficient Std Err t P>|t| 95% confidence interval
LnUNE Coefficient Std Err t P>|t| 95% confidence interval
ARDL Bounds Test
The ARDL Bound test for co-integration, as illustrated in Table 3, evaluates the presence of a long-run relationship among variables by analyzing the F-statistic value against critical bounds If the F-statistic surpasses the upper critical bound, the null hypothesis of a long-run relationship is rejected Conversely, if the F-statistic falls below the lower critical bound, it indicates no long-run association, and the null hypothesis remains unchallenged.
The F-statistics value serves as a crucial indicator for assessing co-integration between variables In this study, the F statistic for the equation INF=f(UNE) exceeds the upper critical bound at the 5% significance level, suggesting a long-run relationship between these variables Conversely, the F statistic for the equation UNE=f(INF) falls below all significance levels, indicating the absence of a long-run relationship.
Table 4 ARDL Bounds Test Result
Estimated equation INF=f(UNE) UNE=f(INF)
Asymptotic Critical Bounds Lower bound I(0) Upper Bound I(I)
Error Correction Model
A co-integration relationship exists between inflation and unemployment when inflation is treated as the dependent variable, indicating the necessity of employing an error correction model The results of the error correction model are presented in Table 5.
LnINF Coefficient Std Err t P>|t| 95% confidence interval
Autocorrelation Test (Breusch-Godfrey LM Test)
The Breusch-Godfrey serial correlation LM Test, as indicated in Table 6, confirms the absence of serial correlation in the model, with the probability of Chi-squared supporting that there are no serial correlations present in the residuals.
Table 6 Breusch-Godfrey Serial Correlation LM Test
Lags Chi2 df Prob > chi2
Lags Chi2 df Prob > chi2
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 2
Table 7 Breusch-Pagan Test for Heteroscedasticity
Normality Test for Residuals
The Jarque-Bera Test indicates that the residuals of the equation \$\text{LnINF} = f(\text{LnUNE})\$ are not normally distributed, while the residuals of the equation \$\text{LnUNE} = f(\text{LnINF})\$ exhibit a normal distribution.
Table 8 Jarque-Bera Normality Test
Stability Test
The Cumulative Sum (CUSUM) Stability Test graphs for the two equations from 1991 to 2020, illustrated in Figure 2, reveal periods of instability This instability is concerning as it indicates that the sample period of the study was not consistently stable.
Figure 4 Cumulative Sum (CUSUM) Stability Test
DISCUSSION AND CONCLUSION
Discussion
This study investigates the co-integration relationship between inflation and unemployment in Vietnam, utilizing the Autoregressive Distributed Lag (ARDL) Bound Test The findings indicate a significant co-integration relationship when inflation is treated as the dependent variable, evidenced by an F Statistic of 6.449, which exceeds the upper critical bound I (1) of 5.73 at a 5% significance level Consequently, this suggests the presence of a long-run relationship between inflation and unemployment in Vietnam.
In this case, the null hypothesis of no co-integration between the variables is rejected
An error correction model was applied to the co-integrated variables, revealing an adjustment coefficient of -0.5326 with a statistically significant p-value of 0.002 This indicates a 53.3% speed of adjustment towards the equilibrium path, meaning that any future deviation from the current inflation equilibrium will decrease by 53.3% in the subsequent period Additionally, the findings suggest that a 1% rise in the unemployment rate leads to a 0.61% reduction in the long-term inflation rate.
The ARDL estimation results indicate that there is an insignificant relationship between inflation and unemployment in both the short-run and long-run A p-value of 0.168, which exceeds the 0.05 threshold, confirms the insignificance of this relationship in the short-run Similarly, a p-value of 0.577 further supports the lack of significance in the long-run relationship between these two variables.
Conclusion
This study investigates the relationship between inflation (INF) and unemployment (UNE) in Vietnam using annual data from 1991 to 2020 An Autoregressive Distributed Lag (ARDL) Model was employed for analysis The findings indicate that unemployment has a negative and insignificant effect on inflation in the short run, while inflation similarly shows a negative and insignificant impact on unemployment However, a co-integration relationship was identified, suggesting a long-run connection between the two variables when inflation is treated as the dependent variable Ultimately, the study concludes that there is a long-run relationship between inflation and unemployment, with unemployment continuing to exert a negative and insignificant influence on inflation over the long term.
The study highlights the need for Vietnamese policymakers to consider the interplay between inflation and unemployment to ensure price stability and lower unemployment rates It emphasizes the importance of long-term strategies that incorporate preventive measures and necessary structural adjustments to effectively manage both economic challenges.
As additional data becomes accessible, future researchers may consider employing ARDL modeling with quarterly or monthly data
Altay, B., Tuğcu, C.T., Topỗu, M (2011) İşsizlik ve enflasyon oranları arasındaki nedensellik ilişkisi: G8 ỹlkeleri ửrneği Afyon Kocatepe ĩniversitesi İİBF Dergisi, 8(2), 1-26
Bayrak, M., Kanca, O.C (2013) Türkiye’de Phillips eğrisi üzerine bir uygulama
Eskişehir Osmangazi ĩniversitesi 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
Bỹyỹkakın, T (2008) Phillips eğrisi: Yarım yỹzyıldır bitmeyen tartışma İ.ĩ Siyasal
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
Carvalho, d., Ribeiro, & Marques (2017) Economic decelopment and infaltion: a theoretical and empirical analysis International Review of Applied Economics,
Chappelow, J (2020) Guide to Unemployment Retrieved from: https://www.investopedia.com/terms/u/unemploymentrate.asp (accessed on 12/23/2021)
Chowdhury, A (2008) Methods explained: the GDP implied deflator Economic &
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
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
Fisher, I (1933) The Debt-Deflation theory of Great Depressions Econometrica, 337 -
Friedman, M (1977) Inflation and unemployment The Journal of Political Economy,
Furuoka, F (2007) Does the Phillips curve really exist? New empirical evidence from
Geronikolau, G., Spyromitros, E., & Tsintzos, P (2020) Progressive taxation and human capial as determinants of inflation persistence Economic Modelling, 82 -
Gujarati, D N (2004) Basic Econometrics 4th Edition The McGraw-Hill Companies
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] Available at https://www.investopedia.com/terms/u/unemployment.asp (Accessed: 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
ILO, IMF, OECD, UNECE, & WorldBank (2004) Producer Price Index Manual IMF
Jahoda, M (1982) Employment and unemployment: A social-psycho logical analysis
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
Laidlier, D (2000) Highlights of The Bullionist Controversy Department of
Economics, University of Western Ontario
Lepetit, A (2020) Asymmetric unemployment fluctuations and monetary policy trade- offs Review of Economic Dynamics, 36, 29-45
Liu, Z & Rudebusch, G (2010) Inflation: Mind the gap FRBSF Economic Letter 2010-
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
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
Ndzwayiba, Anga'Wandisa (2020) What Is Unemployment
Nishizaki, K., Sekine, T., & Ueno, Y (2012) Chronic Deflation in Japan Bank of Japan
Pettinger, T (2019) Definition of Unemployment [Online] Available at https://www.economicshelp.org/blog/2247/unemployment/definition-of- unemployment/ (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
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): 71-
Uysal, D., Erdoğan, S (2003) Enflasyon ile işsizlik oranı arasındaki ilişki ve Türkiye ửrneği (1980-2002) SU İİBF Sosyal ve Ekonomik Araştırmalar Dergisi, 6, 35-
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
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