The relationship between price inflation and unemployment has always been a point of focus for the policy makers. As the historically negative relationship has been observed between inflation and unemployment in many economies which implies that if government seeks to reduce the inflation rate the unemployment goes up and if it wants to enjoy the lower unemployment it has to bear the burden of inflation. The present paper is an effort in this regard to identify this phenomenon for the South Asian Economies which include four countries Pakistan, India, Bangladesh and Sri Lanka. The work has been carried out by taking into account the thirty years historical rates of inflation and unemployment for all four countries. Findings of this paper suggest that there is no relationship between inflation and unemployment on aggregate level. In addition, the separate analysis of each country shows that, the relationship between inflation and unemployment is positive in Pakistan and negative in Bangladesh, while at the same time the independent movement has been observed of the two variables in India and Sri Lanka. The negative impact of rising inflation over unemployment is actually the existence of theoretical Phillips Curve which is evidenced by Bangladesh and it seems to be a result of migration of people towards employment sources. There is no existence of Phillips Curve in Pakistan, India and Sri Lanka.
Key Words: Inflation; Unemployment
Corresponding authors email: [email protected], [email protected], [email protected],[email protected], [email protected]
INTRODUCTION
Phillips Curve shows an inverse relationship between the rate of inflation and the rate of unemployment in an economy. While it has been seen that there is a stable short run tradeoff between these two, but it has not been observed for the longer time. This relationship theory has been tested many times for eastern as well as western economies. Having a number of studies, there is still a contradiction about the theory. The present paper is also an attempt in this regard to identify this relationship in South Asian Countries including Pakistan, Bangladesh, India and Sri Lanka. A sample of 30 years rates of Inflation and Unemployment have been taken for all of the four countries, from the year 1981 to 2010, and Linear Regression Model has been applied to the penal data. It has been evidenced that on aggregate there is no significant relationship between Unemployment and Inflation; however the separate analysis for each country shows that in Pakistan there is a positive relationship between both the variables and in Bangladesh the inflation negatively affects the unemployment, i.e. Bangladesh evidence the existence of traditional Phillips Curve.
LITERATURE REVIEW
Phillips (1958) put the light upon the theory of a kind of tradeoff between the rate of inflation and the rate of unemployment. Phillips describes how he observed an inverse relationship between money wage changes and unemployment in the British economy over the period examined. This relationship depicts that the inflation rate depends insecurely upon the level of unemployment in an economy. Similar patterns were found in the other countries and Phillip's work was further taken by Samuelson and Solow (1960) made the explicit link between inflation and unemployment: when inflation was high, unemployment was low and vice-versa. Fisher (1920) noted this kind of Phillips curve relationship. However, Phillips' original curve described the behavior of money wages. Since the core task of policy-makers of the state is to avoid both high unemployment and runaway inflation, Phillips Curve leaves the choice with the state to choose any one higher and enjoy the lower of other. If we are willing to tolerate high levels of unemployment, simultaneously we can enjoy the low rates of price inflation and vice versa. (For example, to reduce inflation X percent would require the loss of Y jobs and a change of Z percent in growth).
Friedman (1970) argued that the Phillips curve relationship was only a short-run phenomenon, as many countries experienced high levels of both inflation and unemployment in that period. Theories based on the Phillips curve suggested that this could not happen, and the curve came under a concerted attack from a group of economists headed by Friedman. He argued that in the long-run workers and employers will take inflation into account, resulting in employment contracts that increase pay at rates near anticipated inflation. Employment would then begin to fall until "full employment" was reached, but now with higher inflation rates. This result implies that over the longer-run there is no trade-off between inflation and employment. This implication is significant for practical reasons because it implies that central banks should not set employment targets above the natural rate.
Brayton, Roberts and Williams (1999) studied the dependency of price inflation on the unemployment rate, past price inflation, and standard measures of price supply shocks, to identify the factors behind simultaneous occurrence of low falling price inflation and low unemployment in US in that period. The authors took six measures of inflation (including CPI Consumer price index, all items, CPIX Consumer price index, excluding food and energy chain-weight price, PCE Personal consumption expenditures chain-weight price, PCEX Personal consumption expenditures, excluding food and energy, GDP chain-weight price, NFB Nonfarm business, excluding housing, chain-weight price) and put two alternative modifications to the properties of Standard Phillips Curve by first replacing unemployment with capacity utilization and secondly with markup of prices over trend unit labor costs. Authors concluded that Capacity Utilization predicted inflation more accurately than did the unemployment rate, and also the mark up of prices in part explained the inflation movement of that decade. This article can be relevant to our work of research as we could study these variables on the data acquired from our four selected economies.
Another study regarding "Why there is a long run tradeoff between inflation and unemployment and how does it depend on the degree to which wage-price decisions are backward versus forward looking" was conducted by Snower and Karanassou (2002) the authors wanted to identify the impact of price-wage decisions of the different time orientations (i.e.: past wages and prices, and future wages and prices) on the shape of the long run Phillips Curve. The authors specify three aspects in this regard the backward looking, the forward looking and the wage-price contracts and emphasize their analysis on the later aspect. They further comment that when economic agents, facing time-contingent, staggered nominal contracts, have a positive rate of time preference, the current wage and price levels depend more heavily on past wages and prices than those of the future. Consequently the long run Phillips Curve becomes downward sloping. The model used in this study has three building blocks. The first block links unemployment to the real money balances, the second specifies the money supply and the third specifies the response of the wage and price level to the money supply. The authors concluded that when the time discount rate is positive, the backward looking determinants of wage formation have strong influence than the forward looking ones. Therefore an increase in the money growth raises inflation rate and reduces the unemployment rate in the long run. Hence the long run Phillips Curve is downward sloping. This work relates to our study as we would identify long run relationship between inflation and unemployment in south Asian countries.
Another work was done as a new look at the long run dynamics of inflation and unemployment in response to permanent changes in the growth rate of the money supply.
Snower, Sala and Karanassou (2002) examine the Phillips Curve from the perspective of what they call "Frictional Growth" (i.e. the interaction between money growth and nominal frictions). After presenting theoretical models of this phenomenon, they constructed an empirical model of the Spanish economy to identify the interplay between money growth and prolonged nominal adjustment processes. In this context the authors evaluate the long run inflation-unemployment trade off for Spain and examine how recent policy changes have affected it. The analysis rests on three empirical regularities: (i) the growth rate of the money supply is nonzero, (ii) there is some nominal inertia, so that a current nominal variable is slow to adjust to money growth shocks, and (iii) unemployment is influenced by the ratio of the nominal money supply to that nominal variable (such as the ratio of the money supply to the price level). The study was based on three models, the first model describes the real money balance channel," i.e. an increase in money growth affects long-run real money balances and thereby the long-run unemployment rate. The second model considers the real wage channel," whereby an increase in money growth affects long-run unemployment via the real wage and employment. And the third model considers both channels operating together.
Authors suggest a significant role for monetary policy in combating Spanish unemployment in the long run. This role, however, has been reduced somewhat through successive policy changes, particularly the introduction of the Monclova Pacts and Spain's entry into the EEC and possibly the EMS. They further conclude that the monetary policy has had a very substantial and prolonged effect on unemployment and the inflation; the empirical analysis of Spain's long run Inflation-unemployment tradeoff indicates that some of this unemployment effect is permanent.
Blanchflower and Oswald (1994) argue that wages are determined by a "wage curve" that relates an individual's wage to the level of the unemployment rate in their region or industry. They also suggest that these are macroeconomic results and these results can be inconsistent with a macroeconomic Phillips curve. In opposition to Phillips, their evidences suggest that there is a relationship between the level of the wage and the unemployment rate and not the change in the wage. King and Watson (1994) have taken evidence into account and concluded that expectations-augmented Phillips curve is a robust feature of the U.S. macroeconomic data over the past several decades and as a consequence appears to be some tension between individual wage curve and macroeconomic results, but this tension is only apparent tension not the real one.
Empirical evidence suggests that estimates of the slope of the wage curve that are taken from Phillips curves are close to the range of estimates that Blanchflower and Oswald obtain from microeconomic data. The aggregate data may be reflecting the same phenomena as Blanchflower and Oswald are describing. Many macroeconomic text books, such as Hall and Taylor (1993, pp. 597-8) nad Dornbusch and Fischer (1994 p.472), use the term "expectations-augmented Phillips curve" to refer to an aggregate relationship between inflation, expected inflation, and the unemployment rate.
Blanchflower and Oswald also state that "The idea of a Phillps curve may be inherently wrong". The validity of this statement depends on what we mean by the Phillips curve.Their proposition is that Phillips's original model does not apply to an individual data. However this proposition is nonetheless consistent with macroeconomic expectations-augmented Phillips curve.
Blanchard and Katz (1997) in his recent paper, argue Blanchflower and Oswald's empirical evidence that it is the level, rather than the change, in the wage that is related to the unemployment at the macroeconomic level. As Blanchard and Katz point out, if the macroeconomic relationship involves the change rather than the level, it is easy to derive the macroeconomic Phillips curve.
Aggregate Phillips curve can also be derived if Blanchflower and Oswald are correct; an implication is that the form of the microeconomic relationship does not matter for the derivation of the aggregate Phillips curve.
METHODOLOGY
For this research, the historical rates of inflation and unemployment have been acquired from online resources including UNO's official website and Indexmundi website. The analysis utilized simple linear regression model; the test involved regressing dependent variable Unemployment (log transformed) and independent variable Inflation. The following regression was used as a base to show the relationship of inflation with unemployment.
RoU = α + βiRoI + ε
Where,
RoU = the rate of unemployment,
α = the intercept: value predicted by the model,
βi = the coefficient value of the predictor;
RoI = the rate of inflation and
ε = the error term.
RESULTS AND DISCUSSIONS
The following table 1 of ANOVA, tests the acceptability of the model from a statistical perspective. The regression shows that only 31.7% of the variation has been accounted for by the model, although it's greater than the Residual value however the F statistic value is insignificant 0.350. So it can safely be assumed that variation explained by the model may be due to chance.
Table. 1 /2
ANOVAb
Model
Sum of Squares
df
Mean Square
F
Sig.
1
Regression
.317
1
.317
.886
.350a
Residual
23.242
65
.358
Total
23.559
66
a. Predictors: (Constant), Rate of Inflation
b. Dependent Variable: COMPUTE LN_UEmp=LN(Unemployment)
Table. 2/2 ANOVAb
Name of the Country
Model
Sum of Squares
df
Mean Square
F
Sig.
Pakistan
1
Regression
.449
1
.449
2.996
.095a
Residual
3.895
26
.150
Total
4.344
27
India
1
Regression
.024
1
.024
.898
.375a
Residual
.185
7
.026
Total
.209
8
Bangladesh
1
Regression
7.406
1
7.406
8.400
.023a
Residual
6.172
7
.882
Total
13.578
8
Sri Lanka
1
Regression
.102
1
.102
.863
.365a
Residual
2.255
19
.119
Total
2.357
20
a. Predictors: (Constant), Rate of Inflation
b. Dependent Variable: COMPUTE LN_UEmp=LN(Unemployment)
While the ANOVA table is a useful test of the model's ability to explain any variation in the dependent variable, it does not directly address the strength of that relationship.
The model summary table reports the strength of the relationship between the model and the dependent variable. The table 2 of the Model Summery shows, explanation by the model, and 0.116 value of R shows a very week prediction of unemployment through inflation. If we see the R Square 0.013 it shows that only 1.3% of the variation is explained by the model, that is, there is almost none or an overall negligible relationship between inflation and unemployment.
Table .2
Model Summaryb
Model
R
R Square
Adjusted R Square
Std. Error of the Estimate
Durbin-Watson
1
.116a
.013
-.002
.59797
.582
a. Predictors: (Constant), Rate of Inflation
b. Dependent Variable: COMPUTE LN_UEmp=LN(Unemployment)
To see the relative comparison of the relationship between Inflation and Unemployment in all four countries we follow the below given coefficients table 3. In this table we see that three of the four countries' (Pakistan, India and Sri Lanka) coefficients are non-significant indicating the inflation rate does not consider much to the model However Bangladesh is significant predictor. On identifying the relative importance we see that Bangladesh has a very much negative absolute standardized coefficient -0.739, which shows a considerably negative relationship between Inflation and Unemployment, and it clearly depicts from the Unstandardized beta -0.527. This negative value is the pure investigation of Phillips Curve.
Table. 3 Coefficientsa
Name of the Country
Model
Unstandardized Coefficients
Standardized Coefficients
t
Sig.
B
Std. Error
Beta
Pakistan
1
(Constant)
1.477
.167
8.825
.000
Rate of Inflation
.032
.019
.321
1.731
.095
India
1
(Constant)
2.060
.128
16.139
.000
Rate of Inflation
.016
.017
.337
.948
.375
Bangladesh
1
(Constant)
5.562
1.271
4.377
.003
Rate of Inflation
-.527
.182
-.739
-2.898
.023
Sri Lanka
1
(Constant)
2.048
.188
10.895
.000
Rate of Inflation
.015
.016
.208
.929
.365
a. Dependent Variable: COMPUTE LN_UEmp=LN(Unemployment)
CONCLUSION
In the light of above results and our analysis we found that although there is no existence of Phillips Curve in aggregate South Asian economies. However in relative analysis we come to know that there is a slight positive relationship between inflation and unemployment in Pakistan, (which is the reverse case of the Phillips Curve), and a significant negative relationship in Bangladesh. So Bangladesh solely witnesses the existence of Phillips Curve. Logically an increase in inflation rate should also trigger up the unemployment rate which is happening in Pakistan, but in case of Bangladesh the situation is reverse that is when inflation is increasing it cuts down the rate of unemployment. This situation can be the result of migration of the locals for job retention, and people may begin supplementing their income sources to make a tradeoff between their current spending and future requirement.
REFRENCES
Phillips (1958), The Relationship between Unemployment and the Rate of Change of Money Wages in the United Kingdom, 1861-1957: "Economica 57"(1958), pp.283-99
John M. Roberts (1997), The Wage Curve and Phillips Curve, Federal Reserve Board FEDS Paper No 97-57, JEL Classification E31, J22, J41
Dennis J. Snower, Marika Karanassou (2002), "An Anatomy of the Phillips Curve" Discussions Paper No. 365, IZA Germany, JEL Classification E2, E3, E5, J3.
Flint Brayton, John M. Roberts, and John C. Williams, (1999), Federal Reserve System U.S (Finance and Economics Discussion Series) (1999-49)
Marika Karanassou, Hector Sala, Dennis J. Snower, (2002), "Long-Run Inflation-Unemployment Dynamics: The Spanish Phillips Curve and Economic Policy" IZA Germany Discussion Paper No. 645, JEL Classification E2, E3, E4, E5, J3.
http://www.indexmundi.com/bangladesh/unemployment_rate.html
