This study aims to investigate the dependency of the fluctuation of inflation rate of Asian countries on seven indicators, including Broad Money Growth, GDP Deflator, Exchange Rate, Interest Rate, Wage and Salaried Worker, Population Growth and Countries Income Levels from 2011 to 2021 with the econometrics approach. The researchers collected data from World Bank, host countries’ Statistic Department, Asian Development Bank, Trading Economics and analyzed data using STATA software to carry out Pooled Ordinary Least Square regression with DriscollKraay standard errors. The findings showed that monetary factors (Board Money Growth and Interest Rate) exert a more considerable impact on the fluctuation in inflation rate than other variables in the model. Overall, the regression model is statistically significant with 1% significance level, and six independent variables (Broad Money Growth, GDP Deflator, Exchange Rate, Interest Rate, Wage and Salaried Worker and Countries Income Levels) have statistical impact on inflation rate, at 1% and 5% significance level, except for Population Growth rate. After reporting and discussing the results in detail, the authors proposed policies at the governmental level with the aim of controlling the inflation rate at a consistent level and stabilizing the economy for Asian countries. Keywords: inflation, econometrics, panel analysis, Asia.
https://tailieuluatkinhte.com/ FOREIGN TRADE UNIVERSITY FACULTY OF INTERNATIONAL ECONOMICS -*** MIDTERM Module: ASSIGNMENT Econometrics DETERMINANTS OF INFLATION RATE A PANEL ANALYSIS OF ASIAN ECONOMIES FROM 2011 TO 2021 Class: KTEE318 Group: Instructor: Dr Đinh Thị Thanh Bình Hanoi, June 2023 ABSTRACT This study aims to investigate the dependency of the fluctuation of inflation rate of Asian countries on seven indicators, including Broad Money Growth, GDP Deflator, Exchange Rate, Interest Rate, Wage and Salaried Worker, Population Growth and Countries Income Levels from 2011 to 2021 with the econometrics approach The researchers collected data from World Bank, host countries’ Statistic Department, Asian Development Bank, Trading Economics and analyzed data using STATA software to carry out Pooled Ordinary Least Square regression with Driscoll-Kraay standard errors The findings showed that monetary factors (Board Money Growth and Interest Rate) exert a more considerable impact on the fluctuation in inflation rate than other variables in the model Overall, the regression model is statistically significant with 1% significance level, and six independent variables (Broad Money Growth, GDP Deflator, Exchange Rate, Interest Rate, Wage and Salaried Worker and Countries Income Levels) have statistical impact on inflation rate, at 1% and 5% significance level, except for Population Growth rate After reporting and discussing the results in detail, the authors proposed policies at the governmental level with the aim of controlling the inflation rate at a consistent level and stabilizing the economy for Asian countries Keywords: inflation, econometrics, panel analysis, Asia TABLE OF CONTENT Chapter THEORETICAL FRAMEWORK .8 Overview of Inflation 1.1 Definition of Inflation 1.2 Classification of Inflation 1.3 Causes of Inflation Overview of Determinants of Inflation rate .10 2.1 Board money growth 10 2.2 GDP Deflator 10 2.3 Exchange rate 10 2.4 Interest rate 10 2.5 Salaried workers 11 2.6 Population growth .11 2.7 Countries Income Levels 11 Literature review 12 Research hypotheses 13 Chapter METHODOLOGY AND MODEL SPECIFICATION 14 Methodology 14 Theoretical model specification .14 2.1 Model specification 14 2.2 Variables explanation 15 Data statistical description .15 Chapter ESTIMATED MODEL AND STATISTICAL INFERENCES .18 1.1 Estimated model 18 Diagnosing the problems of the model .18 1.2 Estimation result .20 Hypothesis testing 21 2.1 Significance of independent variables 21 2.2 Overall significance of the model .21 Mechanism relationships between variables 21 3.1 Broad money growth 21 3.2 GDP Deflator 22 3.3 Exchange rate 22 3.4 Real interest rate 22 3.5 Wage and salaried workers .23 3.6 Population growth .23 3.7 Countries Income Levels 23 Recommendations 24 LIST OF TABLES Table 1.1 WB countries classification in terms of income (2022-2023) 11 Table 2.1 Description of variables 15 Table 2.2 Descriptive statistics results 15 Table 2.3 Correlation coefficient matrix 17 Table 3.1 Estimation result 20 LIST OF FIGURES Figure 1.1 Demand-pull inflation Figure 1.2 Cost-push inflation INTRODUCTION Macroeconomics holds the theory that the overall level of price in an economy adjusts to bring money supply and money demand into an equilibrium point When the central bank increases the supply of money, it causes the price level to rise Persistent growth in the quantity of money supplied leads to continuing inflation Inflation can be so low that people not pay any attention to it, as has been the case for the U.S over recent decades It can be moderate, where people pay attention to inflation and change their economic behavior because of it Inflation can also be so high that it causes significant problems in the working of the economy In order to have an accurate viewpoint on the fluctuation of inflation rate of Asian countries in the past decade, we conducted research on the topic “Determinants of Inflation Rate: A Panel Analysis of Asian Economies from 2011 to 2021”. Our research objective is to identify the factors that could have an impact on the inflation rate of all Asian nations between 2011 and 2021 and to clarify the dependency of inflation rate on these factors Hence, the research question should be stated as follows “What is the relationship between inflation rate and broad money growth, GDP deflator, exchange rate, interest rate, wage and salaried workers, population growth, country income levels within Asian countries from 2011 to 2021?” The object of our research is the inflation rate of 46 countries in Asia and seven indicators of inflation rate, which are: Broad Money Growth, GDP Deflator, Exchange Rate, Interest Rate, Wage and Salaried Workers, Population Growth and Country Income Levels The research scope includes content scope, time scope and spatial scope The content scope is researching on factors affecting inflation rate in Asian countries The time scope of the data in this research is from 2011 to 2021 The spatial scope is the geographical territory of 46 countries This research consists of main chapters as follows, Chapter 1: Theoretical Framework, Chapter 2: Methodology and Model Specification, Chapter 3: Estimated Model and Statistical Inference CHAPTER THEORETICAL FRAMEWORK Overview of Inflation 1.1 Definition of Inflation Inflation is a sustained increase in the general price level of goods and services in an economy over a period of time, or sustained reduction in the purchasing power per unit of money – a loss of real value in the medium of exchange and unit of account within the economy Computing method: πt= CPI t −CPI t −1 ×100 % CPI t −1 Where t is the year that inflation rate is calculated and CPI is the consumer price index 1.2 Classification of Inflation Moderate Inflation: inflation rate smaller than 10%/year, prices increase slowly Moderate inflation can spur production because price increases lead to higher profit for enterprises, therefore, firms will increase quantity Galloping Inflation: inflation rate is from 10% to 99% per year This type will destroy the economy and curb the engines of the economy Hyperinflation: defined as inflation that exceeds 100% percent per year Costs such as shoe-leather and menu costs are much worse with hyperinflation– and tax systems are grossly distorted Eventually, when costs become too great with hyperinflation, the money loses its role as store of value, unit of account and medium of exchange Bartering or using commodity money becomes prevalent Expected inflation: depends on the expectation of individuals about government expenditure in the future Its impact is small but helps to adjust production cost Unexpected inflation: derives from exogenous shocks and unexpected factors inside economy 1.3 Causes of Inflation Demand-pull inflation is caused by continuing rises in aggregate demand (AD) in the economy The increase in AD may be caused by either increases in the money supply or increases in government expenditure when the economy is close to full employment In general, demand-pull inflation is typically associated with a booming economy Figure 1.1 Demand-pull inflation Source: (Barth & Bennett, 1975) Cost-push inflation is associated with continuing rises in costs Rises in costs may originate from a number of different sources such as wage increases and other higher costs of production Figure 1.2 Cost-push inflation Source: (Barth & Bennett, 1975) Overview of Determinants of Inflation rate 2.1 Board money growth Velocity and the quantity equation M×V=P×Y Where: M: Quantity of money V: Velocity of money P × Y: Dollar value of the economy’s output of goods and services It is called the quantity equation because it relates the quantity of money (M) to the nominal value of output (P × Y) The quantity equation shows that an increase in the quantity of money in an economy must be reflected in one of the other three variables: The price level must rise, the quantity of output must rise, or the velocity of money must fall In many cases, it turns out that the velocity of money is relatively stable 2.2 GDP Deflator The GDP deflator is one measure that economists use to monitor the average level of prices in the economy and thus the rate of inflation In Macroeconomics, it is calculated as follow: GDP deflator= Nominal GDP ×100 Real GDP Because nominal GDP and real GDP must be the same in the base year, the GDP deflator for the base year always equals 100 The GDP deflator for subsequent years measures the change in nominal GDP from the base year that cannot be attributable to a change in real GDP 2.3 Exchange rate Exchange rate is the rate at which a person can trade the currency of one country for the currency of another The rate of inflation in a country can have a major impact on the value of the country's currency and the rates of foreign exchange it has with the currencies of other nations However, inflation is just one factor among many that combine to influence a country's exchange rate 2.4 Interest rate The very concept of an interest rate necessarily involves comparing amounts of money at different points in time To understand how much a person earns in a savings account, we need to consider both the interest rate and the change in the prices The interest rate that measures the change in currency amounts is called the nominal interest rate, and the interest rate corrected for inflation is called the real interest rate The nominal interest rate, the real interest rate, and inflation are related approximately as follows: Real interest rate=Nominal interest rate−Inflation rate 2.5 Salaried workers Salaried workers are those who work for employers in the public or private sector and receive compensation in forms of salary They are recognized as an eminent and skilled component of the labor force, the majority of whom are mature-age and work in the industry and service sectors where labor productivity and labor standards are better assured The size and proportion of salaried workforce reflect the level of the labor market growth, and the dynamics of salaried workforce reflect the dynamics of the economy, especially under the context of economic recession The employment trends of salaried labor force are an indicator of the “health” of the economy This factor is not included in many previous studies; however, after running the model, the authors found a relationship between this variable and inflation rate Thus, we believe that this could be worth considering in future policies to control inflation 2.6 Population growth Population growth can be defined as the increase in the number of people in a given area The three main factors that affect population growth are fertility rate, life expectancy, and net immigration 2.7 Countries Income Levels The World Bank assigns the world’s economies to four income groups - low, lower-middle, upper-middle, and high income The classifications are based on the GNI per capita of the previous year GNI measures are expressed in United States dollars (USD), and are determined using conversion factors derived according to the Atlas method The latest thresholds (2022 - 2023) for Atlas GNI per capita are as follows: Table 1.1 WB countries classification in terms of income (2022-2023) Group 2022 for FY23 2021 for FY22 Low income < 1,085 < 1,045 Lower-middle income 1,086 - 4,255 1,046 - 4,095 Upper-middle income 4,256 - 13,205 4,096 - 12,695 High income > 13,205 > 12,695 Source: World Bank 12 CHAPTER ESTIMATED MODEL AND STATISTICAL INFERENCES Estimated model 1.1 Diagnosing the problems of the model Tests the existence of factor The study tests the existence of factor in the research model by Breusch-Pagan Lagtangian multiplier test with two research hypotheses H0: a i does not exist H1: a i exists The research results show that: chibar2(01) = 520.60 Prob > chibar2 = 0.0000 p-value < 0.05 (5%), at the 5% level of significance, the hypothesis H1 is accepted and the model has the existence of factor Therefore, the Fixed-effects model (FEM) / Random effect model (REM) is more suitable for the research data than the Pooled regression model Test whether the unique errors are correlated with the regressors The study continues to test whether the unique errors are correlated with the regressors in the model by Hausman test with the research hypothesis: H0: Difference in coefficients not systematic The research results indicate that: chi2(6) = (b-B)'[(V_b-V_B)^(-1)](b-B) = 39.75 Prob>chi2 = 0.0000 The above results show p-value = 0.0000 < 5%, at the 5% significance level, rejecting hypothesis H0, and the model that fits the research data is the FEM fixedeffects model 13 Test of heteroskedasticity The study continues to conduct a defect test of heteroskedasticity using a modified Wald test in a fixed-effects model The research null hypothesis is: H0: sigma(i)^2 = sigma^2 for all i The research results are as follows: chi2 (46) = 2.2e+05 Prob > chi2 = 0.0000 p-value = 0.0000 < 5%, so at 5% significance level, reject hypothesis H0, the model has heteroscedasticity defect Test for serial correlation - autocorrelation The study continues to conduct the Wooldridge test for serial correlation autocorrelation in panel data H0: no first-order autocorrelation The results indicate that: F(1, 45) = 12.871 Prob > F = 0.0008 p-value < 5%, at 5% significance level, reject the hypothesis H0, the model has serial correlation defects in panel data Test for cross-sectional correlation Finally, the study conducts the Pesaran's test for cross-sectional correlation in panel data H0: no cross-sectional correlation The results indicate that: Pesaran's test of cross sectional independence = 2.101, Pr = 0.0356 Average absolute value of the off-diagonal elements = 0.346 p-value < 5%, so at 5% significance level, reject the hypothesis H0, the model has serial-sectional correlation defects in panel data 14 1.2 Estimation result Since the original research model has some violations, the authors fix it using the command: xtscc INF BRM GDPD FX IR WAGE PO low lowmid upmid Estimated results by Stata with pooled OLS method with 506 observations are shown in the table below Table 3.1 Estimation result INF Coef Std Err t P >|t| BRM 1719*** 0128 13.47 0.000 GDPD 0088*** 0007 12.47 0.000 FX (.00009)*** 00001 (5.63) 0.000 IR (.8923)*** 0703 (12.69) 0.000 WAGE (.0342)** 0114 (2.99) 0.013 PO 0980 0902 1.09 0.303 low 3.5859** 1.4324 2.50 0.031 lowmid 3.4056*** 5294 6.43 0.000 upmid 2.3606*** 5777 4.09 0.002 _cons 6.0048 1.2525 4.79 0.001 Observations 506 Coefficient of determination 0.9175 F (9, 10) 10599.67 Pro > F 0.0000 INC Source: STATA 15 Hypothesis testing 2.1 Significance of independent variables The *, ** and *** after coefficients show the significance of the variables respectively with level of significance 10%, 5% and 1% All independent variables have significant impact on the dependent variable Inflation rate (INF), except Population Growth (PO) 2.2 Overall significance of the model With F= 10599.67 and p-value (Fs) < 0.0001, the model has an overall significance at l0%, 5% and 1% level of significance Mechanism relationships between variables 3.1 Broad money growth Broad money growth, according to the estimation, has a positive impact on the inflation of nations A coefficient of 0.1719 indicates that when BRM increases by 1%, INF will increase by 0.17% This result is consistent with our expectation since broad money is the amount of money circulating in an economy (Investopedia), its increase would create inflation within that economy The result is also supported by some former studies Camen (2006), in his analysis of Vietnam’s economy for the period 1996-2005 concluded that excess money played a key role in Vietnam's inflation for the 1990s However, studies by Hung (1999) on Vietnam’s inflation from 1990 to 1995 indicate that the effect of money supply on inflation is modest and incomplete On a broader scale, the research of 13 industrial countries by Dewald (2003) shows that BMG does affect nominal inflation but not real inflation These results suggest the possibility that the impact of the BROAD MONEY on inflation may vary across periods of time 3.2 GDP Deflator The estimated result suggests that GDP deflator positively affects inflation For each unit added to GDP deflator, given other factors stay unchanged, inflation increases by 0.0088% This result is expected by the authors and follows mentioned theories As GDP deflator “measures the changes in prices for all the goods and services produced in an economy” (Investopedia), its increase thus leading to inflation