# The Impact of Inflation on Share Prices of Tobacco Industry

## 1.1 Overview

The economies of the world highly depend on the environment and surrounding. These include various economic and social factors as well, which affect the businesses. The share price of any firm is also dependent on such variables beside a company's own profitability and performances. In past researches, it has been observed that the rate of inflation is inversely proportional to the share prices in developing countries, while this relationship is somewhat neutral in developed countries such as USA and UK, Lessard (1980) suggested. In any case, there has been a long-term impact of inflation on stock prices.

## 1.2 Research Problem

Inconsistent behavior of stock market and share price has been observed in different countries with respect to the Consumer Price Index (CPI). Furthermore, type of industry is another factor which results in variation of the behavior. This study analyzes the impact inflation (CPI) accounts for, specifically on the share price of tobacco industry of KSE-100 index in Pakistan.

## 1.3 Hypotheses

H1: CPI Predicts Share Price for Pakistan Tobacco.

H2: CPI Predicts Share Price for Lakson Tobacco.

H3: CPI Causes Share Price for Pakistan Tobacco.

H4: CPI Causes Share Price for Lakson Tobacco.

H5: CPI of Today explains the CPI of future.

H6: Today’s Share Prices of Pakistan Tobacco explain the future share prices of Pakistan Tobacco.

H7: Today’s Share Prices of Lakson Tobacco explain the future share prices of Lakson Tobacco.

## 1.4 Outline of the Study

The research studies the impact of consumer price index (CPI) on the share price of tobacco industry in Pakistan. The research also studies the positive or negative impact of inflation, and the extent to which inflation affects the share prices of KSE-100 index tobacco companies.

## 1.5 Definitions

## Consumer Price Index (CPI)

Price index is used for measuring inflation. It measures price level with respect to a selected base year. There are different kinds indices used for measuring inflation. Consumer price index (CPI), sensitive price index (SPI), and wholesale price index (WPI) are used in Pakistan.

This research is based on consumer price index (CPI) which measures the price level at retail level, directly impacting the consumer's spending and saving behavior. CPI in Pakistan is calculated using retail prices of 374 items in 35 cities.

## CHAPTER 2:

## LITERATURE REVIEW

Several authors have previously analyzed the relationship between inflation and share prices.

Cohn and Lessard (1980) found that there is a negative relationship between nominal inflation and share prices in many countries. From investor’s point of view, it is hard to trace the factors which are playing influencing part along with inflation in changing the stock market behavior. It was also found that factors including change in risk-free rate which affects long term earnings, variation in risk premium, and the variation in actual growth. It was also observed that there were systematic errors at investors end while calculating stock prices when there was high inflation.

Crosby and Otto (2000) analyzed inflation and its impact on capital stock using time-series data of many countries, and found that there is a long-term impact of inflation on capital stock in most countries where inflation is not super neutral. In most cases, it was quite difficult to trace any relationship between the two when there is neutral inflation behavior in a country. It also revealed that most economists consider a negative relationship between stock market and inflation. The reason for such behavior is due to inclusion of both public and private stock in analysis, while both stocks usually have different responses to the inflation. Inclusion of both created a thin line between near-to-none relation and a positive long-term impact.

It was suggested that individual countries must be analyzed first, reason stated, different factors are exclusive to countries which accounted as one of the reason. Interest, taxation, and impact of other economic factors on capital markets including private and public, can be treated separately and differences can be identified for a reliable analysis.

Garber (1982) argued that the hyperinflation in Germany resulted in some transition costs which were the results of non-subsidizing of investments in private sector. Similar behaviors from state authorities lead to a positive relationship among private stocks and the inflation. Furthermore, different treatments of tax department's nominal interest deductions and depreciation often results in such relationship between the two variables within a country.

Durre and Giot (2005) used Fed model to test the relationship between stock prices, earnings, and interest rates while aiming at the possibility of a long-term relationship. Fed model relates the government bond yield of 10 years with stock yield. It also argued the theoretical flaws of the model, and arrived at opinion that it does not take into account the issue of inflation illusion correctly. Therefore, its result incorrectly show lowered stock prices with the increase in inflation. While on the other hand, low inflation results in higher Price-to-earnings ratio.

During the analysis of 13 countries by Durre and Giot (2005), results showed that there is undoubtedly a long-term relationship among earnings, stock prices, and bond yield in more developed countries such as United States and United Kingdom. But, the bond yield's relationship is not considerably significant, and therefore it does not affect stock market equilibrium significantly. Considering the short term impact, a relationship between stock returns and bond yield was found. It was due to the reason that most analyst emphasize on valuation ratios such as price-to-earnings ratio. Argument that low earning yields and high stock prices are the result of low interest rates was proved wrong.

Examining the relationship among macroeconomic variables and stock market, Adam and Tweneboah (2008) revealed that macroeconomic variables such as inflation, interest rates, net foreign direct investment and exchange rate have a significant impact on share prices in the long run. This long-run analysis was tested using Johansen's multivariate co-integration test. It also revealed the positive correlation between inflation and share prices. Similar findings were from Anari and Kolari (2001) where results also revealed that stock market provides hedge against inflation, while long-term relation was evident among inflation and share prices.

Comparing interest rates, FDI, exchange rate and inflation as an impacting factor on share prices, as tested by Adam and Tweneboah (2008), the interest rates affects the share prices more significantly than inflation and therefore it was an indicator for investors to pay attention on interest rates. Foreign Direct Investment and Exchange Rate's impact were next in line. CPI's impact is minimal when compared to those macroeconomic variables.

Analysis of relation between inflation and real stock returns by Day (1984) showed a consistent negative correlation between the two variables. It argued that inflation is directly created and controlled by economy's supply of money by government. Analyzed was the market with equilibrium and rational investors. The opinion varied when it studied the relation of other economic factors and relationship beyond just inflation and asset pricing. The model suggests the variability in asset pricing and it implies that consumption and investment decision of a firm results in variability in consumption which is lower than the total output. The rational expectations and market efficiency were seen consistent with the variability of asset prices.

Fama (1981) is of the opinion that there is a negative relationship between share prices and inflation. It argued that this is because of a prominent negative linkage among inflation and real activity. While, positive relation is found between share prices and real activity. Since the 3 variables are linked to each other, the final share prices and inflation have an inverse relation. Later the evidence is mixed when negative coefficient turns insignificant in the regression after base money growth is also added to the model. Nevertheless, the share prices always reacted negatively to the inflation. On the other hand, the movement of share prices is considered positive with inflation since returns from real assets are claimed to be real returns. Therefore, the shares are considered a hedge against inflation.

Kool and Hafer (1986) research based on the findings of Fama (1981) and argued that negativity of stock prices and inflation is because of a inverse correlation between unexpected inflation and the output. Evaluating the post-1950 period it is found that real activity has an impact on share prices and the impact of inflation on share prices is quite different from zero. Post 1980 results favor the Fama Hypothesis. While, the results from pre-1950 period goes straight in favor of orthodox theory where a positive correlation between real activity and stock returns noticed dominating the inflation impact and future activity.

New York Stock Exchange Index declined by 68 percent during 1965 to 1981, and the dividends and returns were fallen close to zero during the period. As suggested by Fama (1981), the higher inflation rate is the main reason that caused such downfall in the market. It was also observed that tax system was also to be blamed for higher inflation which resulted in share price issue.

Feldstein and Martin (1980) also argued that tax system is somehow responsible for the inflation. Historic cost method of depreciation and capital gain taxation are the factors which cause the stock returns to fall with the increase in inflation. While, it also decreases the value of the debt a firm holds, and therefore the return on bonds are also reduced. The expectation of increase in tax and inflation has an effect to some extent on share prices.

Another reason was debated by Malkiel (1979) suggesting that the decline of Stock Exchange in USA occurred while there was an evident risk of capital investments during 1970s. It shows that impact on a firm's capital due to gross marginal return increased after 1965 which also resulted in the riskiness of investor' returns from holding stocks. Increase volatility of stock returns is also observed which shows the variance of return on NYSE Index. During the period, variance continued to increase, and this fluctuations caused variation in firm's gross marginal return on capital and increment in variance of inflation as well. Unforeseen events, such as, fluctuations in regulatory, exchange rate, and competition of market players, that affect capital gains and losses are usually unrealized. Thus, it makes it difficult to measure the return on capital smoothly. But, the variance can still be calculated from the data available at stock markets. Malkiel is of the opinion that whatever these fluctuations do, but it definitely affect the business environment and makes it more uncertain.

Fama (1981) results also points indirectly to the correlation real economic variables and gross marginal return on capital. The volatility of gross return is linked to the volatility of inflation, which has a negative correlation with returns when unanticipated. On another end, volatility is also responsible for riskiness of bonds. Though, it is unclear if this volatility increases the share value while making bonds riskier, and not the other parameters such as tax rates.

Pindyck (1983) found that behaviour of gross marginal return on capital is the actual reason affecting share prices. Analysis discusses that there are controversies regarding the variance since results showed it doubled while other authors are of the opinion that expectation of return fell. The two changes actually depend on how investors consider this risk and make decisions accordingly, analysis suggests. Developed model is simple and only utilized asset returns, asset demands, and share prices. Though, the model limiting factors were known to be reliance on rational share valuation, income streams in consumption, and consideration of only two assets in portfolios. Use of a partial equilibrium framework was also another limiting factor. These limitations made it difficult to analyze the results but to an appreciable extent, it proved that share price increases when there is an increase in capital stock, while there is a negative relation between inflation and returns.

Investor's perception of risk is another issue Pindyck considers difficult to measure. Analysis emphasized that it can be measured to a good acceptable level using sample variance of stock market returns, but the use of survey data is even better in measuring it. Analysis also argued that non-negligible probability of economic catastrophe makes the capital risky even if the volatility in stock returns does not exist.

Subhani (2010) found that there is a relationship between KSE-100 Index and CPI. Though, the relationship is negative. Analysis also found that it is participant's perception which causes inconsistent effect to trading. Participant’s response to the CPI announcements varies and causes declining trade volume variably.

Schwert (1981) analyzed daily stock returns and concluded that any unexpected inflation or a negative news regarding stock market reacts in a negative response from stock market as well. Meaning, if inflation rises, the stock price falls.

Feldstein (1983) found that higher inflation rate results in decreasing ratio of share prices to before-tax earnings. The main factors that cause it are historic-cost depreciation and the increasing tax on capital gains. Both factors, caused by inflation, decrease the return on capital. It also revealed that investors are often responding differently to tax related news, and at times the share prices fall even if the demand price per share is increased by inflation.

## CHAPTER 3:

## RESEARCH METHODS

## 3.1 Method of Data Collection

Secondary data was used for conducting this research. Data of consumer price index (CPI) was collected from Federal Bureau of Statistics (statpak.gov.pk) and Economic survey of Pakistan. Share prices of Pakistan Tobacco Company and Lakson Tobacco Company was collected from ksestocks.com and Taurus Securities, a capital management firm.

## 3.2 Sample Size

A sample of 238 observations has been used in the study. Monthly consumer price index from January 1991 to October 2010 has been used. CPI is taken as base year set to 1991. While daily share price of tobacco companies were converted into monthly averages for the same period. Yearly data with 20 observations was analyzed to compare the results with monthly analysis.

## 3.3 Research Model

Same model is used for predicting the share price of Pakistan Tobacco Company and Lakson Tobacco.

SPί = α + β1(INFί) + β2(INFί2) + β3(INFί3) + ε

Where, SP is Share Price of the company, INF is rate of inflation, ί is selected case, α is constant, and ε is error.

Models for both companies were developed for two scenarios, data without auto-correlation, and data having auto-correlation.

Auto-correlation was removed by applying square root on rate of inflation and share prices, and log transformation on transformed variables. Removal of auto-correlation resulted in following models.

Model for Pakistan Tobacco:

(Yearly) SPPakTobacco = -0.444 + 0.161(INFί) + 0.469(INFί2) + 0.073(INFί3)

(Monthly) SPPakTobacco = -0.440 + 0.360(INFί) + 0.443(INFί2) – 0.440(INFί3)

Model for Lakson Tobacco:

(Yearly) SPLaksonTobacco = 0.002 + 1.398(INFί) - 0.008(INFί2) – 0.220(INFί3)

(Monthly) SPLaksonTobacco = 0.048 + 1.428(INFί) - 0.040(INFί2) – 0.225(INFί3)

Auto-correlation was present in non-transformed variables. Following models were created when auto-correlation was not removed.

Model for Pakistan Tobacco:

(Yearly) SPPakTobacco = 258.940 – 2.986(INFί) + 0.012(INFί2) – 0.000001(INFί3)

(Monthly) SPPakTobacco = 242.534 – 2.654(INFί) + 0.010(INFί2) – 0.000001(INFί3)

Model for Lakson Tobacco:

(Yearly) SPLaksonTobacco = 725.421 – 11.521(INFί) + 0.054(INFί2) – 0.0000068(INFί3)

(Monthly) SPLaksonTobacco = 424.803 – 7.050(INFί) + 0.035(INFί2) – 0.0000043(INFί3)

## 3.4 Statistical Technique

Statistical technique used in this research is “Cubic Regression”. Data is transformed into new variable with square root transformation, and then log transformation on that transformed variable, to remove the auto-correlation. Two variables are taken into account for each model and share price of both tobacco companies are predicted separately. Having said this, two variables used in each model are share price and rate of inflation, both are having cubic relation.

## CHAPTER 4:

## RESULTS

## 4.1 Findings and Interpretation of the results

## Yearly Data

Analysis was first done on yearly data and then on monthly data. Data had to be transformed since it was not following normal distribution and to remove auto-correlation.

## Table 4.1.1

## Tests of Normality

Kolmogorov-Smirnova

Shapiro-Wilk

Statistic

df

Sig.

Statistic

df

Zscore(t_cpi)

.079

20

.200*

.981

20

Zscore(t_pakt)

.091

20

.200*

.974

20

Zscore(t_lakt)

.157

20

.200*

.943

20

Sig values of Shapiro-Wilk suggest that data is normal.

## Pakistan Tobacco

## Table 4.1.2

## Model Summary

R

R Square

Adjusted R Square

Std. Error of the Estimate

.741

.550

.465

27.029

## Table 4.1.3

## ANOVA

Sum of Squares

df

Mean Square

F

Regression

14275.152

3

4758.384

6.513

Residual

11689.029

16

730.564

Total

25964.180

19

With the presence of auto-correlation, model summary suggests that cpi explains 55% of share price for Pakistan Tobacco. The suggested model is also considered fit since sig value in ANOVA table is less than 0.05

## Table 4.1.4

## Model Summary

R

R Square

Adjusted R Square

Std. Error of the Estimate

.624

.390

.276

.851

## Table 4.1.5

## ANOVA

Sum of Squares

Df

Mean Square

F

Regression

7.409

3

2.470

3.409

Residual

11.591

16

.724

Total

19.000

19

After applying transformation, cpi explains 39% of share price for Pakistan Tobacco, while the model is considered fit. But, the sig value in ANOVA table is not far below 0.05.

## Lakson Tobacco

## Table 4.1.6

## Model Summary

R

R Square

Adjusted R Square

.947

.897

.877

## Table 4.1.7

## ANOVA

Sum of Squares

Df

Mean Square

F

Regression

363646.177

3

121215.392

46.359

Residual

41835.309

16

2614.707

Total

405481.485

19

With auto-correlation presence, consumer price index explains 89.7% of share price for Lakson Tobacco. Sig value of ANOVA is also less than 0.05. Therefore, the model is considered fit.

## Table 4.1.8

## Model Summary

R

R Square

Adjusted R Square

Std. Error of the Estimate

.940

.884

.862

.372

## Table 4.1.9

## ANOVA

Sum of Squares

Df

Mean Square

F

Regression

16.787

3

5.596

40.452

Residual

2.213

16

.138

Total

19.000

19

After auto-correlation is removed, cpi explained 88% of share price for Lakson Tobacco. The model is also considered fit since the sig value is less than 0.05.

## Table 4.1.10

## Correlations

Zscore(t_cpi)

Zscore(t_pakt)

Zscore(t_cpi)

Pearson Correlation

1

.309

Sig. (2-tailed)

.184

N

20

20

Pearson Correlation suggests that there is a high correlation between Lakson Tobacco share price and CPI. But the correlation is not prominent between cpi and share price of Pakistan Tobacco.

## Monthly Data

Raw data did not have normality while auto-correlation was present. Data was transformed using square root and log transformation which converted the data into normal distribution and auto-correlation was removed.

## Table 4.1.11

## Tests of Normality

Kolmogorov-Smirnova

Shapiro-Wilk

Statistic

df

Sig.

Statistic

df

Zscore(ln_sqrt_cpi1991)

.055

238

.081

.977

238

Zscore(ln_sqrt_PakTobaccoSharePrice)

.055

238

.078

.974

238

Zscore(ln_sqrt_LaksonTobaccoSharePrice)

.148

238

.000

.950

238

Kolmogorov-Smirnov suggests that consumer price index and share price of Pakistan Tobacco is normal. The mean and median for share prices of Lakson Tobacco fell close, and within the range of 5%. Therefore, it was considered for further statistical tests.

## Pakistan Tobacco

## Table 4.1.12

## Model Summary

R

R Square

Adjusted R Square

Std. Error of the Estimate

.708

.501

.494

27.575

## Table 4.1.13

## ANOVA

Sum of Squares

df

Mean Square

F

Regression

178539.001

3

59513.000

78.265

Residual

177934.110

234

760.402

Total

356473.111

237

With the presence of auto-correlation, Model Summary suggested that rate of inflation explains 50% of share price for Pakistan Tobacco, while the model is also considered fit since sig value of ANOVA is less than 0.05.

## Table 4.1.14

## Model Summary

R

R Square

Adjusted R Square

Std. Error of the Estimate

.611

.373

.365

.797

## Table 4.1.15

## ANOVA

Sum of Squares

df

Mean Square

F

Regression

88.485

3

29.495

46.472

Residual

148.515

234

.635

Total

237.000

237

After applying transformations, which removed the auto-correlation, Model Summary for share price of Pakistan Tobacco and rate of inflation reveals that rate of inflation explains 37% of share price for Pakistan Tobacco. Having considered this, it does not actually cause the share price in the market.

Sig value of ANOVA table is less than 0.05, which means that regression model for predicting share price of Pakistan Tobacco is suitable.

## Lakson Tobacco

## Table 4.1.16

## Model Summary

R

R Square

Adjusted R Square

Std. Error of the Estimate

.853

.728

.724

78.413

## Table 4.1.17

## ANOVA

Sum of Squares

Df

Mean Square

F

Regression

3847422.758

3

1282474.253

208.578

Residual

1438786.372

234

6148.660

Total

5286209.129

237

The presence of auto-correlation in share prices of Lakson Tobacco revealed that the rate of inflation explains 72% of the share price for Lakson Tobacco. While, the model is considered fit having the sig value of less than 0.05 in ANOVA table.

## Table 4.1.18

## Model Summary

R

R Square

Adjusted R Square

.928

.861

.859

## Table 4.1.19

## ANOVA

Sum of Squares

df

Mean Square

F

Regression

204.119

3

68.040

484.213

Residual

32.881

234

.141

Total

237.000

237

After the removal of auto-correlation, rate of inflation explains 86% of share price for Lakson Tobacco. Comparing with Pakistan Tobacco, Lakson Tobacco is more responsive to rate of inflation in the economy.

ANOVA table having sig value of 0.000, which is less than 0.05, states that regression model is suitable for predicting share price of Lakson Tobacco.

Beside rate of inflation, other economic factors indeed impact the behavior of stock market. Therefore, CPI alone is not considered a significant predictor of share prices for tobacco industry in Pakistan.

## Table 4.1.20

## Correlations

Zscore(ln_sqrt_cpi1991)

Zscore(ln_sqrt_PakTobaccoSharePrice)

Zscore(ln_sqrt_cpi1991)

Pearson Correlation

1

.327**

Sig. (2-tailed)

.000

N

238

238

Pearson correlation reveals that there is a positive correlation between consumer price index and share price of tobacco industry, but this relation is not very prominent. While, on the other hand correlation between consumer price index and share price of Lakson Tobacco is strong and positive.

Auto-correlation test for consumer price index (CPI), share price of Pakistan Tobacco, and share price of Lakson Tobacco, tested with 16-lags, have auto-correlation value between 0.5 and 1, while sig value is 0.000 through-out the cases. It states that today’s CPI, share price of Pakistan Tobacco, and share price of Lakson Tobacco explain the future rate and prices for at least 16 months.

Study of monthly and annual data resulted in no considerable variations. Therefore, results are considered having similar behavior among monthly and annual analysis.

## Figure 4.1.1

Figure 4.1.1 reveals the trend of share prices of Pakistan Tobacco and Lakson Tobacco. It suggests that Pakistan Tobacco prices with relation to the CPI, raised in the beginning. It fell, and then again increased at the end. While, the Lakson Tobacco started to rise late, and fell after very short span of time. Trend of both companies are showing growth in recent past, but at lower level.

## 4.2 Hypotheses Assessment Summary

## Yearly

## Hypotheses

## B1

## B2

## B3

## Sig

## Result

CPI Predicts Share Price for Pakistan Tobacco.

.161

.469

0.073

.043

Accepted

CPI Predicts Share Price for Lakson Tobacco.

1.398

-.008

-0.220

.000

Accepted

CPI Causes Share Price for Pakistan Tobacco.

.161

.469

0.073

.043

Rejected

CPI Causes Share Price for Lakson Tobacco.

1.398

-.008

-0.220

.000

Rejected

## Hypotheses

## Autocorrelation

## (16 lags)

## Sig

## Result

CPI of Today explains the CPI of future.

.772 > x > -.370

(for Lag1) (for Lag16)

.000

Accepted

Today’s Share Prices of Pakistan Tobacco explain the future share prices of Pakistan Tobacco.

.667 > x > -.005

(for Lag1) (for Lag16)

.000

Accepted

Today’s Share Prices of Lakson Tobacco explain the future share prices of Lakson Tobacco.

.867 > x > -.263

(for Lag1) (for Lag16)

.000

Accepted

## Monthly

## Hypotheses

## B1

## B2

## B3

## Sig

## Result

CPI Predicts Share Price for Pakistan Tobacco.

.360

.443

-0.440

.000

Accepted

CPI Predicts Share Price for Lakson Tobacco.

1.428

-.040

-0.225

.000

Accepted

CPI Causes Share Price for Pakistan Tobacco.

.360

.443

-0.440

.000

Rejected

CPI Causes Share Price for Lakson Tobacco.

1.428

-.040

-0.225

.000

Rejected

## Hypotheses

## Autocorrelation

## (16 lags)

## Sig

## Result

CPI of Today explains the CPI of future.

.979 > x > .697

(for Lag1) (for Lag16)

.000

Accepted

Today’s Share Prices of Pakistan Tobacco explain the future share prices of Pakistan Tobacco.

.977 > x > .503

(for Lag1) (for Lag16)

.000

Accepted

Today’s Share Prices of Lakson Tobacco explain the future share prices of Lakson Tobacco.

.983 > x > .712

(for Lag1) (for Lag16)

.000

Accepted

## CHAPTER 5:

## DISCUSSIONS, CONCLUSION, IMPLICATIONS AND FUTURE RESEARCH

## 5.1 Conclusion

The research found that there is a positive correlation between consumer price index and share price of tobacco industry in Pakistan. Consumer price index does explain the share price for Pakistan Tobacco and Lakson Tobacco, but it only predicts the portion of it. Other economic factors are also responsible for the change, and that is the reason CPI does not cause the share prices alone. Study revealed that current trend of tobacco industry in stock market explains the future trends.

## 5.2 Discussion

Various studies analyzed that there is a negative relationship between stock market and inflation, while there were many economies there was positive relation, but in both cases, the relationship was prominent in long-term. Consumer price index in Pakistan has a direct impact on consumers as well as businesses, and it has been a key issue for couple of decades. The reason for relatively different impact of inflation on stock market in Pakistan when compared to other economies of the world is behavior of people towards inflation. Increasing inflation results in increase in price of commodities that should have an impact, but it also affects non-related commodities and industries.

Inflation and share value of every month has links with the values of past and future. Thus, it also reveals that the change of rates and prices are not only affected by the economic factors, but the values itself are predictors of the values of future.

## 5.3 Implications and Recommendations

Analysis and model of this research can be a good use for financial analysis and researches. It not only helps in studying the relationship between inflation and stock market, but also helps in investing decisions for investors willing to buy shares. For better and more accurate predictions, other economic factors must also be included in the research, making the analysis and investing decisions more reliable for investors and consultants.

## 5.4 Future Research

This research provides a base for predicting share prices of tobacco industry in Pakistan with response to the change in rate of inflation. Share price for other industries and companies can also be predicted using the developed model. Other economic factors can also be included in the research in future, to predict the stock market behavior more accurately.

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