0115 966 7955 Our phone lines are closed today, but you can still place your order online
Place an Order
Instant price

Struggling with your work?

Get it right the first time & learn smarter today

Place an Order
Banner ad for Viper plagiarism checker

Impact of Inflation and Real Wages on Labor Productivity

Disclaimer: This work has been submitted by a student. This is not an example of the work written by our professional academic writers. You can view samples of our professional work here.

Any opinions, findings, conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of UK Essays.

Published: Tue, 12 Dec 2017

1.1 Overview

The study attempts to determine the relationship between inflation, real wages and labor productivity. Inflation is an increase in the average level of prices of goods and services in an economy over a period of time, not a change in any specific price. When the general price level rises; each unit of currency buys fewer goods and services. Output is the amount of goods and services by a firm, industry, or country. For output variable the index of value added is used. Nominal wages are the Average Annual Earning in Perennial Industries. Real wages are the wages that have been adjusted for inflation. Real wages are obtained by deflating the nominal wage index by the consumer price index (CPI).

1.2 Problem Statement

The objective of the study is to find out the impact of Inflation & Real wages on Labor Productivity.

1.3 Hypotheses

H1. There is an Impact of Inflation on Labor productivity

H2. There is an Impact of time on Labor productivity

H3. There is an Impact of Real wages on Labor productivity

H4. There is an Impact of time on Real wages.

1.4 Outline of the study

The scope of this research was to find out the impact of inflation and real wage on labor productivity.

The data was collected from state bank of Pakistan and through various websites.

CHAPTER 2:

LITERATURE REWIEW

Malik and Ahmed, (2001) studied that Information on income levels was essential in evaluating the living standards and conditions of work and life of the employees. Since nominal income failed to explain the purchasing power of employees, real income was considered as a major indicator of employee’s purchasing power and was used as proxy for employee’s level of income. Any variation in the real wage rate had a significant impact on poverty and the distribution of income. When used in relation with other economic variables, for instance employment or output they were valuable indicators in the analysis of business cycles.

The aim of the adjustment program was to increase national income or output in such a way that it resulted in fair distribution of wealth. That was, the two objectives of enhanced growth and reduced poverty were being followed through more efficient use of resources and policy instruments like exchange rates adjustment, monetary and fiscal policies, and banking sector reforms to improve cash-flow position (Irfan, 2008).

The relationship between real wages and output was intricate and also inconclusive. Regardless of the truth, which method of estimation was used or which deflator was used for the real earnings the results remained the same. Only different time periods (for the manufacturing sector) have changed the cyclical nature of the real earnings. For the manufacturing sector the real earnings had turned out to be counter-cyclical. While for agriculture, transport and communication, construction and the overall economy real earnings is pro-cyclical, i.e., real earnings tend to increase with economic growth and increases in real earnings rate tend to reduce poverty. It’s the other way round in the manufacturing sector. It’s important to mention here that the measure of nominal earnings used for manufacturing was different from the measure used for other sectors and the overall economy (Irfan, 2008).

Productivity was the fundamental determinant of distinction in living standards, often measured as GDP per capita, across countries and across regions within a country. Over a longer term, productivity growth was the only way to sustain improvements in living standards or quality of life (Krugman 1994). It provided the economic base for investment in education, environmental improvement, health, infrastructure, poverty reduction, and social security. In addition, it was a key determinant of international competitiveness. Given its importance, improving productivity had become an essential national agenda for many countries. That had led to an emphasis on understanding factors that lead to higher, or lower, productivity growth in both research and strategy (Tang and Wang, 2004).

Individual industrial contributions to cumulative labor productivity increase, which often requires decomposing cumulative labor productivity increase into industrial components. When real output was additive, that is, the cumulative real output was equal to the sum of the real outputs of its industries, the decomposition was straight forward. The only problem was that the decomposition was susceptible to the choice of base year. In other words, an industrial contribution calculated based on base year t was different from that based on base year s. That takes places because output prices change over time at different paces across industries. (Tang and Wang, 2004)

It was usually expected that industries with high productivity growth and thus declining real output prices attract demand and accordingly increase employment shares. Why do the observed facts in the two countries run against this expectation? One possible explanation was that ‘income effects had reduced the demand for manufactures, which broadly speaking became a satisfied market whereas the expansion, especially of personal service, suffered from rising relative prices’ (ten Raa and Schettkat, 2001). Another possible explanation was that increased female labor force contribution resulted in a substitution of market purchased served for home produced services’ (Grubel and Walker, 1989).

An industry’s input from an increase in relative size to aggregate labor productivity growth could be wellbeing improving or reducing, depending on its causes. For example, if an increase in the real output price of an industry hence an increase in its relative size was caused by an increase in demand for the output of the industry (an upward shift in the output demand curve), then it was wellbeing enhancing, because it increased both consumer and producer surpluses. On the other hand, if an increase in real output price was caused by a decrease in output supply (e.g., due to a natural disaster) or an upward move in the output supply curve (e.g., due to an increase in production costs from events such as real earnings increases), then it was wellbeing reducing, because it reduces both consumer and producer surpluses. Thus, from a wellbeing perspective, failure to report for the causes of change in relative size could create a confusing perception of an industry’s contribution to aggregate labor productivity (Tang and Wang, 2004).

Taylor (1990) found that the value of productivity in an open economy was distributed among at least three parties: Profit recipients, workers and the rest of the world. There are two key nominal prices: the exchange rate, which is established by policy, and the money wage, which follows from institutional considerations. A change in one with the other constant is bound to have effects on distribution and productivity, by changing the profit share, the real wage or the real exchange rate.

In an open economy in which non-competitive intermediate imports were an important component of cost, currency devaluation derived up prices and reduced the real earnings. Output reduction could easily follow if exports were not strongly elastic to exchange rate changes. When devaluation is contractionary, then money earnings increases make output to go up. Under such circumstances, a successful tight money policy that derived down nominal earnings to ratify the equation of exchange reduced output and improved the trade account. The reduction had been offset by fiscal growth, but in an orthodox stabilization attempt that has been a strange move. (Taylor, 1990)

Prices did not rise before the earnings demands had been made and accepted: in a large segment of a modern economy prices were administered ones. Thus in these segments excess of demand evident itself in deficiency rather than in a rise of prices, as the over riding objective of maximizing profits over time (and the fear of price wars) keep oligopolistic competitors from meeting excess demand by increasing prices to the short-run maximum. Thus there were always un-liquidated monopoly increases which permit earnings increases (and which would be taken once a general increase of costs reduces the inhibition against raising prices (Balogh, 1958).

A detailed analysis of production, productivity, earnings and prices, both in domestic and in international dealings, irresistibly and increasingly leads away from the explanation of the continuous raise in current prices here and somewhere else by the excess of money demand, and in particular by the raise in the volume of money.

Separately no entrepreneur could grant wage increases as it was difficult to bypass the addition to costs by increasing prices. But if all (or most) entrepreneurs were faced with almost the same wage demands, and react to them in more or less with the same manner, experience has taught that it was safe to agree to those demands: it was the increase in income due to the wage bargain (including of course the increased profit) that provided the additional demand required to sell output at the improved price. There was no need to hypothesize a hidden, unspent or dormant, excess demand which became ‘active’. The myth of those who were looking for the unseen and unseen able was that all applied the ceteris paribus (With all other factors or things remaining the same) method to a situation where it was changed by itself because it was of a limited and not of a minute magnitude. Provided that the process was general, as it was, and repetitive, as it was bound to be, if single earnings good deal overshoot the average, as they were bound to do, there was nothing to stop it from speeding up its velocity as anticipations of further earnings and prices increased enlarge speculation (Balogh, 1958).

CHAPTER 3:

RESEARCH METHODS

3.1 Data Collection

The data was collected from state bank library and searched through various internet search engines e.g. jstor and Google scholar for articles, index mundi and UN website.

3.2 Sampling Technique

Convenience sampling was used as data was not collected from the companies but it was collected from state bank of Pakistan.

3.3 Sample Size:

30 annual observations of real wages, inflation and labor productivity are taken for this study.

3.4 Research Model

The following research model was used

Labor productivity = α + β (real wage)

LP= -1.472E12+3.3909E11RW

3.5 Statistical Technique

Regression analysis was applied.

CHAPTER 4:

RESULTS & ANALYSIS

4.1 FINDINGS AND INTERPRETATIONS

H1. There is an Impact of Inflation on Labor productivity.

Table 4.1

ANOVA

Sum of Squares

Df

Mean Square

F

Regression

6.022E21

1

6.022E21

.001

Residual

2.623E26

27

9.713E24

Total

2.623E26

28

The independent variable is CPI inflation.

Impact of inflation on labour productivity is studied through curve estimation. As data was not normal, linear, ln , exponentiate , inverse transformation was applied. Significant relationship was not found even after applying transformation as it is evident by the sig value of .98 which is greater thatn .05.

H2. There is an Impact of time on Labor productivity

Table 4.2

Model Summary

R

R Square

Adjusted R Square

.998

.995

.995

The independent variable is YEAR.

Table 4.3

ANOVA

Sum of Squares

Df

Mean Square

F

Regression

81.851

1

81.851

7528.575

Residual

.391

36

.011

Total

82.242

37

The independent variable is YEAR.

Table 4.4

Coefficients

Unstandardized Coefficients

Standardized Coefficients

t

B

Std. Error

Beta

YEAR

.134

.002

.998

86.767

(Constant)

2.282E-104

.000

.

The dependent variable is ln(All Industries output).

There is a positive impact of time on labour productivity.

Sig value is less than .05 therefore it is significant. It means there is an Impact of time on labour productivity. Its constant value is < .05 and it is significant. Its F value is 7528.57. Its Adjusted R Square is .995

H3. There is an Impact of Real wages on Labor productivity.

Table 4.5

Model Summary

R

R Square

Adjusted R Square

.862

.743

.732

The independent variable is realwage.

Table 4.6

ANOVA

Sum of Squares

Df

Mean Square

F

Regression

7.068E25

1

7.068E25

69.357

Residual

2.446E25

24

1.019E24

Total

9.513E25

25

The independent variable is realwage.

Table 4.7

Coefficients

Unstandardized Coefficients

Standardized Coefficients

T

B

Std. Error

Beta

ln(realwage)

3.909E11

4.694E10

.862

8.328

(Constant)

-1.472E12

4.929E11

-2.986

LP= -1.472E12+3.3909E11lnRW

As its sig value is < .05 therefore it is significant and its f value is 69.35. Its constant is also significant. Its adjusted r2 is .732 and its F value is 69.357

H4. There is an Impact of time on Real wages.

Table 4.8

Model Summary

R

R Square

Adjusted R Square

.728

.529

.510

The independent variable is YEAR.

Table 4.9

ANOVA

Sum of Squares

Df

Mean Square

F

Regression

244.833

1

244.833

26.998

Residual

217.648

24

9.069

Total

462.481

25

The independent variable is YEAR.

Table 4.10

Coefficients

Unstandardized Coefficients

Standardized Coefficients

t

B

Std. Error

Beta

YEAR

.409

.079

.728

5.196

(Constant)

-805.624

156.901

-5.135

Sig value is less than .05 therefore it is significant. It means there is an Impact of time on Real wages. Its F value is 26.99. Its Adjusted R Square is .510

4.2 HYPOTHESES TESTING

After applying the statistical test and based on the p (sig.) values, researcher has obtained all the tables and results have been provided in the following table three hypotheses were accepted and one hypothesis was rejected.

4.2.1 ACCEPTED HYPOTHESES

H2, H3 & H4 is the accepted hypotheses.

4.3 HYPOTHESIS ASSESSMENT SUMMARY

Table 4.11

Hypothesis

R Square

F

Significance Value

Empirical Conclusion

H1: There is an Impact of Inflation on Labor productivity

.001

.98

Rejected

H2: There is an Impact of time on Labor productivity

.995

7528.57

.000

Accepted

H3: There is an Impact of Real wages on Labor productivity

.743

69.357

.000

Accepted

H4: There is an Impact of time on Real wages.

.529

26.998

.000

Accepted

CHAPTER: 5

DISCUSSIONS, IMPLICATIONS, FUTURE RESEARCH AND CONCLUSIONS

This study empirically tested the relationship of inflation, real wage and labor productivity Inflation and real wage were the measures which are the predictors of Labor productivity.

Initial estimation was that there is an impact of inflation on labor productivity, there is an impact of time on labor productivity, there is an impact of real wages on labor productivity and there is an impact of time on real wages.

Jarret and Selody (1982) had considered that inflation and productivity growth are negatively related. Inflation diminished the incentive to work, distorted the informational content of relative price levels, and contracted tax reductions for depreciation. Studies suggested there was a negative relationship between inflation and productivity.

It was assumed that there is a positive relationship between real wages and productivity because higher real wages increased the opportunity cost of job loss and stimulated greater work effort to avoid job loss. That positive relationship was also assumed because higher real wages put upward pressure on labour costs and cause firms substituted capital for labour, thus increasing the marginal productivity of labour (Wakeford, 2004).

The results supported the conclusion that inflation has no effect on the labor productivity as its analysis showed it is not significant after applying regression analysis. Real wage have significant impact on labor productivity and real wage have positive relationship with labor productivity. Its results showed that relationship between Real wages and labor productivity is significant and 74% of variation (table 4.5) in labor productivity was explained by Real wages. Where as time has a positive relationship with real wage as well as with labor productivity.

Further research should be carried out to study the relationship of inflation and labor productivity in the future as other variables (which could have relationship with inflation) are not included in this research.


To export a reference to this article please select a referencing stye below:

Reference Copied to Clipboard.
Reference Copied to Clipboard.
Reference Copied to Clipboard.
Reference Copied to Clipboard.
Reference Copied to Clipboard.
Reference Copied to Clipboard.
Reference Copied to Clipboard.

Request Removal

If you are the original writer of this essay and no longer wish to have the essay published on the UK Essays website then please click on the link below to request removal:


More from UK Essays