Determinants of the effective tax rate Student: Mircea ... · Determinants of the effective tax rate Student: Mircea Bogdan Coordinator: Vintila Georgeta Abstract The fiscal burden

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Determinants of the effective tax rate

Student: Mircea Bogdan

Coordinator: Vintila Georgeta

Abstract

The fiscal burden of a company is the subject of many studies in the economic field. The

concept concerning this paper is the effective tax rate (also noted as ETR) which, in the opinion

of many economics, gives a better imagine of a company’s fiscal burden than the statutory tax

rate. The purpose of this paper is to give an imagine of the national and international opinions for

the ETR regarding the method of calculation and the econometrical models that reflects its

factors. In this paper I presented the most important national and international articles whose

base topic was the effective tax rate and its determinants such as company’s characteristics (like

ROE, ROA, leverage, size) and macroeconomics factors like inflation rate or others. The study

case was based on the Romanian companies listed to the Bucharest Stock Exchange, for the

period 1999-2011, for 12 activity sectors. The results showed some overall influence at the level

of the characteristics of companies and for the macroeconomics factors, but the sectorial analyses

are quite different, the differences being at the level of the limitations of the study.

Keywords: effective tax rate, determinants, fiscal influence, fiscal policy, econometrics,

Romanian companies

Introduction

Taxes have existed since ancient times and it is believed to have occurred in the evolution

of human society in the first state formations, being determined by the need for maintenance of

those materials exercising public power, performing management tasks. Taxes have been

designed differently, influenced especially by social and economic development and public

spending supported by each state.

Income tax is the "cost of doing business." The effective income tax rate may affect

corporate saving rate and cost of capital and in turn the growth rate of a country. To the extent

that countries impose fiscal burdens on taxation, tax can contribute to inflows and outflows of

capital from a country, affecting the cost of doing business in that country.

Effective tax rate includes all taxes and fiscal obligations incurred by a taxpayer. The tax

burden is influenced by sector of activity, the existence of deductibles and fiscal incentives from

the state. Determinants of effective tax rate are the features highlighted by company size, market

share, the performance of it, and macro elements that affect the overall economy, sectorial

influences being of course different.

Literature review

Literature and studies presented below support a stronger influence of the effective tax

rate to the statutory regarding investment and financing decisions.

Impact of effective tax rate and the determinants are subject to numerous case studies on

international and national level that focus on microeconomic sphere. The calculation and

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estimation vary from author to author, and distribution channels impact financial results. Thus, in

order to form an idea of the concept of effective rate of taxation, I presented various national and

international articles with a significant contribution to the literature.

S. Gupta, K. Newbery (1997) studies the determinants of variability effective tax tax at

company level in the period before and after the tax reform of 1986. Number of firms taken in

the analysis was 823 during 1982-1985 and 915 during 1987-1990). Tax reform in the U.S., in

1986, simplified tax code and removed some deductions (income tax rate was reduced from 46%

to 34%, and personal income tax from 50% to 28%). This reform was the most significant

change in the tax structure of America in the last 50 years.

This study shows that the effective tax rate is not associated with firm size when the

relationship is examined over time for companies with long histories. Despite this, results show

that the effective tax rate is negatively correlated with capital structure, elements of assets and

positively correlated with firm performance (ROA), these correlations continued after the 1986

tax reform.

A study published by Kim A.K. and Limpaphayom P. (1998) applies the hypothesis of

positive relationship between effective tax rate and firm size in the context of emerging

economies: Hong Kong, Korea, Malaysia, Taiwan and Thailand. The sample was composed of

372 companies from Hong Kong, 601 in Korea, 361 in Malaysia, 251 in Taiwan and 246 in

Thailand.

Contrary to U.S. studies, the results obtained by the authors show that there is a negative

relationship between effective tax rate and firm size in emerging economies.

The independent variables were represented: total assets, leverage ratio, market value and

profitability of the firm defined as the income to sales (profit margin). In the analysis it is

observed that for the margin of profit, the correlation coefficients are positive and statistically

significant (except Malaysia). The effective tax rate is negatively correlated with firm size,

although this contradicts previous studies, leverage and market value have low significance in

relation to the tax rate.

B. Janssen and Buijink W. (2000) study the existence of an association between

changes in effective average tax rate (ETR) and firm characteristics such as size, asset structure,

existence with foreign operations, performance, leverage, whether the fact that a company stock

is listed or not, or if the company is public. The database included financial information for the

period 1994-1998, comprising 879 firms and 4395 observations.

The study was a model with panel data, regression used is defined as:

ETRt = α

t + β

1FSIZE

t + β

2CAPINT

t + β

3INVINT

t + β

4FOREIGN

t + β

5ROA

t + ß

6 LEVERAGE +

β7LISTED

t + ß

8PUBLIC + ε

t.

In conclusion, through a cross-sectional study panel, including financial data for Dutch

companies, it was attempted to determine the factors that influence the effective tax rate, using

variables that incorporates characteristics of firms and the variables control. Study results

confirmed that the Dutch corporate tax system provides significant amounts of tax deductions to

companies, yet it is fair and neutral, the average effective tax rate is not related to company

characteristics.

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Janssen B. (2005) investigates the actual size of the Dutch tax incentives to companies

using data from the financial statements of 1592 companies in the period 1994-1999. The paper

tries to find solutions to two problems, namely the impact of tax incentives provided by the

Dutch government on corporate tax burdens, and the importance of the impact of certain types of

companies.

The author uses the effective tax rate in the analysis, as the ratio of tax and accounting

profit before tax as the dependent variable and independent variables firm size, capital intensity,

the ratio of foreign sales in total sales, ROA and leverage.

Correlations between effective tax rate and the explanatory variables are mostly

insignificant, and when significant, are small (correlation with ROA is significant, but low, as

well as capital intensity). The results indicate that the Dutch tax system provides few tax

incentives for companies, the differences between statutory rates and effective tax rates are

relatively low.

Also R. Lanis and Richardson G (2007) study the determinants of effective tax rate

variability at micro level, concerning on tax reform in Australia.

The database is the panel that contains financial information for the period 1997 - 2003

for 92 companies. Year 2000 is the year of tax reform which is considered transitional year as

research studies in the field and has been removed from the database.

The econometric model presented in this paper is:

After running the two regressions based on the method of calculation of the effective tax

rate was achieved a degree of determination of 13% for ETR model (1) and 19% for ETR model

(2), both models are validated statistically.

In both econometric models, there was a significant negative correlation with SIZE, LEV,

CINT, RDINT, TREF, TREF * INVINT, TREF * ROA and a significant positive correlation

with INVINT and TREF * LEV.

The study attempted to observe the variability of factors influencing effective tax rate, an

important factor is firm size, which is a negative correlation. Also, negative association has been

observed between ETR and leverage, research and development expenditures intensity. After tax

reform in Australia, it was observed that the ETR continues to be influenced by firm size, capital

and assets structure.

K. Crabbe et. all (2010) study the impact of costs related to the audit and tax advice on

the effective tax rate for large Belgian companies. More specifically, they want to analyze the

relationship mentioned above since it was implemented the corporate governance code in 2003.

The database is composed of Belgian firms' financial data for the period 1999-2007.

Study results indicate that tax advisory expenses does not affect ETR, instead it is influenced by

hiring a BIG4 in order to reduce it. Since the corporate governance code was implemented,

hiring auditors affects ETR rate lower than before its implementation. Influence auditors

expenditure on ETR is approximately 1%.

The econometric model is as follows:

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The final conclusions are:

companies that have a high intensity of capital, leverage and high costs of research and

development, also have a lower effective rate of taxation;

Tax advice variable is statistically insignificant in every regression model tried by the

authors. This shows that additional payments on tax advice do not reduce the effective

tax rate. In contrast, hiring Big4 auditor leads to a reduction in the effective tax rate by

approximately 1%.

Sebastian Lazar (2010) studies for non-financial companies listed on the Bucharest Stock

Exchange in the period 2000-2009 the correlation between actual and statutory taxation rate.

The database was developed using the financial statements of companies listed on the

Bucharest Stock Exchange. The author chose to use the consolidated data to capture specific

influences and determined the tax code contained in Romania. A problem in case studies using

data from Romania is the unavailability and unreliability of financial information, Mr. Lazar

calling Infin database covering over 60 of the non-financial firms listed on the stock exchange.

The case study begins with 2000 being when the Romanian firms have begun to report their

financial statements in accordance with International Standards of Accounting and Regulatory

Accounting Directives. Also, 2000 was the year of tax reform, the state's share of income tax fell

from 38% to 25%.

The effective tax rate is calculated using two major approaches: one based on the accounting

information and the other based on tax information. In this case, Romania, given the tax and

accounting, the author adopted the method of accounting information: ETR = CIT / PI * 100,

where CIT is tax, while PI is gross profit.

In the study, the author revealed the following:

The effective tax rate was below the legal level, with the exception of 2009, the

companies benefiting from tax deductions. In 2005, when the statutory rate fell from 25%

to 16%, there was a significant decrease in the effective tax rate to the pre-2005 as the tax

base has increased. The difference between actual and law rate may be correlated with

certain financial ratios (ROA, ROE, and NPM), showing a negative correlation of -0.636

between ROA and the gap between the rates at a significance level of 5%. The coefficient

of determination is 40%

After an analysis of the sector, to the constant in the trade sector benefiting from the best

tax regime with an effective tax rate of approximately 15%, while the energy sector is the

most heavily taxed, with the effective tax rate to about 31.4%.

Lee N. and C. Swenson (2012) investigate the common factors of influencing the tax base

effective tax enforcement, through an analysis of international tax regimes. In this paper, it

specifically examines the determinants of effective tax rate to 86 advertising companies

operating in the Member States of the European Union, being selected companies listed on the

stock exchange.

The period of analysis is 2005-2007 after, designating 2004 when companies were forced

standardized reporting of financial statements in accordance with IFRS. The database derived

from the Compustat Global requiring adjustments to the indicators that were expressed in the

currency of the country of origin of the company, they are converted into indices in relation to

total assets or turnover as appropriate.

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The effective tax rate is the ratio of current income tax expense and net income before tax,

both the method and the tax accounting.

The econometric model took into consideration is defined as: ∑ ∑

Conclusions are:

companies in countries with high statutory rate have a higher effective rate of tax, the

effective tax rate variation was explained 36% by 1% change in the statutory tax rate

STR;

variables LEV, PPE, INV, Rdinv are statistically significant, reducing the effective rate

of taxation;

Regression model is statistically significant on 1% level of relevancy.

Vintilă G. et al (2012b), in a globalized economy and the lack of stability of the input, it

generates a public issue of corporate involvement in social responsibility actions.

The purpose of this study is to investigate empirically whether how a corporation deals with

corporate social responsibility influence the level of aggressiveness of tax, on the example of

Romanian companies listed on Bucharest Stock Exchange.

Using financial information for the year 2010 for 40 Romanian corporations listed, it is

examined the association between corporate social responsibility and tax aggressiveness.

Hypothesis testing is that the companies who undertake more social responsibility activities are

less aggressive in terms of fiscal, while socially irresponsible firms have a higher tax

aggressiveness.

To investigate the correlation CSR - tax aggressiveness, as a measure of tax

aggressiveness is used effective tax rates and as a level of employment in responsibility activities

it is used the corporate social responsibility index determined on data from annual reports . The

effective tax rate was determined as the ratio of corporate tax and the gross result of company.

The model is:

Conclusions are:

based on probabilities, two (for a significance level of 5%) and three (for a significance

level of 10%) of the seven variables are statistically significant (TROUBLE, INVINT,

respectively GROWTH), while the other variables, with very high probability, are not

statistically significant;

it is noted that the empirical results of the regression analysis for Romanian companies

does not outstand the correlation between tax aggressiveness and corporate social

responsibility, critical probability associated to the independent variable is very high, the

coefficient is regarded as having, statistically speaking the value zero.

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Database

In this study, I selected a sample of 62 companies listed on the Bucharest Stock Exchange

for the period 1999-2011. Selection criteria for Romanian companies were consistent with the

methodology studies, excluding from the sample all firms belonging to the financial sector and

financial intermediation due to specific regulations.

The initial data was:

• Turnover;

• Long-term liabilities;

• Net Profit;

• Gross profit;

• Inventory;

• Total revenues;

• Total expenses;

• Fixed assets;

• Current assets;

• Number of employees;

• Cash;

• Equity;

• Capital.

For this study I calculated the followings indicators:

- ETR calculated in 2 methods: the first as ratio between Corporate Income Tax and Gross Profit

and the second as ratio between Corporate Income Tax and Turnover

- INVINT: inventory intensity represents the amount of inventory related to total assets. I chose

this indicator as a determining factor for the size of the effective tax rate, according to specialists

in the related articles.

- CINT: fixed asset intensity calculated as the ratio between fixed assets and total assets. I chose

this indicator to enter the study, since according to the literature is an important feature in

addressing factors influencing the ETR.

- ROA

- ROE

- Leverage

- Borrowing rate as the ratio between the difference of total assets and equity and total assets

- Corruption Perception Index

- Inflation Rate

- Fiscal year reform dummy variable named “Year”

- Size of the company as the natural logarithm of assets.

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Data analysis

Descriptive statistics

The descriptive statistics is presented below :

We can observe the maximum, minimum and medium values for our variables.

Regarding the normal distribution of the series, according to Jarque-Bera test, our series are not

normal distributed. Also, we can observe that for our data, there weren’t big deviation of the

values from their mean.

Correlation matrix

As can be seen, the coefficients of different variables are small, with few exceptions.

Inflation rate is negatively correlated strongly with the Corruption Perception Index and

positively correlated with ROA. ROA is negatively correlated strongly with the leverage ratio;

also there is a strong correlation between leverage and ROE and between INVINT and CINT.

Size of the company is positively correlated with the number of employees, the leverage ratio

and negatively correlated to the inflation rate.

IPC Inflatia ROA ROE LEVIER INVINT CINT SALARIATI RATA ÎND. SIZE

Mean 3.2308 0.1703 0.0399 0.0447 1.1226 0.1775 2.1463 1744.717 41.66954 17.87849

Median 3.1 0.0899 0.0336 0.062 0.5495 0.1559 1.8227 703.5 38.29 17.73687

Maximum 3.8 0.458 0.6265 10.7245 194.5925 3.178 10.737 81075 167.96 23.54171

Minimum 2.6 0.0484 -1.1668 -24.4835 -94.6573 0 1.0195 1 -0.33 13.47005

Std. Dev. 0.4198 0.1467 0.1106 1.2993 10.3564 0.1565 1.213 6651.331 25.0935 1.541986

Skewness 0.1338 1.0777 -1.3542 -8.627 10.8453 9.1496 3.1111 9.1091 0.955955 0.811736

Kurtosis 1.4402 2.57 23.1806 185.3851 229.7759 169.6999 16.0733 92.9621 4.607983 4.792807

Jarque-Bera 84.11697 162.2148 13923.4 1127124 1742902 944488.2 7039.973 282942.2 209.5938 195.7252

Probability 0 0 0 0 0 0 0 0 0 0

Sum 2604 137.2432 32.1823 36.0243 904.8044 143.0915 1729.949 1406242 33585.65 14356.43

Sum Sq. Dev. 141.8369 17.3334 9.8467 1358.992 86340.27 19.7092 1184.395 3.56E+10 506895.3 1906.931

Observations 806 806 806 806 806 806 806 806 806 806

Cross sections 62 62 62 62 62 62 62 62 62 62

CINT INFLATIA INVINT IPC LEVIER RATA ÎND. ROA ROE SALARIAȚI SIZE

CINT 1 -0.104 -0.4431 0.0821 -0.051 -0.3184 -0.165 -0.0269 0.0775 -0.024

INFLATIA -0.104 1 0.055 -0.4945 0.0162 0.0602 0.2023 0.0247 0.0766 -0.3586

INVINT -0.4431 0.055 1 -0.0463 0.0518 0.3091 -0.0671 -0.034 -0.0467 -0.0367

IPC 0.0821 -0.4945 -0.0463 1 -0.0263 -0.0418 -0.2165 -0.0142 -0.0606 0.1999

LEVIER -0.051 0.0162 0.0518 -0.0263 1 0.0945 -0.0363 -0.8593 -0.0074 -0.0397

RATA ÎND. -0.3184 0.0602 0.3091 -0.0418 0.0945 1 -0.3776 -0.043 0.0191 0.2792

ROA -0.165 0.2023 -0.0671 -0.2165 -0.0363 -0.3776 1 0.0855 -0.0244 -0.1078

ROE -0.0269 0.0247 -0.034 -0.0142 -0.8593 -0.043 0.0855 1 -0.0095 0.0215

SALARIAȚI 0.0775 0.0766 -0.0467 -0.0606 -0.0074 0.0191 -0.0244 -0.0095 1 0.4441

SIZE -0.024 -0.3586 -0.0367 0.1999 -0.0397 0.2792 -0.1078 0.0215 0.4441 1

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Evolution of the effective tax rates ETR1 and ETR2 in Romania

In Romania, the statutory tax rate was 38% in 2009, 25% in 2000-2004 and 16% from

2005 to the present.

At the aggregate level of the analyzed companies, the highest values of average effective

tax rates were recorded in 1999, the average effective tax rate ETR1 in value of 37.15%, while

ETR2 was worth 3.33 %. Also, during the period 1999-2005, ETR1 was lower than statutory,

followed in 2005-2006 to record values exceeding the statutory rate, returning to trend after 2007

initially. Regarding effective tax rate ETR2, we see recorded values below the statutory rate for

the full analysis. In table 1 in Appendix, we can both aggregate and sectorial evolution of ETRs.

The analysis by sector of activity during the period under review, we conclude that the

sectors most affected by the tax are: transport and storage, construction, while the least affected

sectors are tourism, energy. Also the economic crisis has affected all sectors of Romania, the

impact being found in poor financial situations resulting high effective tax rates.

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Econometrical analysis

The base model is as follows :

The results from Eviews are showed in the following table:

Regarding the first regression model, we can observe a positive and significant

correlation between ETR1 and inflation rate, leverage, ROE (for a significance level of 10%),

invetory intensity. The other variables are not significant econometric as probabilities for the test

Student are greater than the level of significance taking into account (5%). A negative correlation

is observed between ETR1 and borrowing rate.

The whole model is valid for a test Fisher probability is greater than 5% and the degree of

determination is 20.77% meaning that the effective tax rate variation ETR1 is explained in the

proportion of 20.77% by the variables included the model; the remaining variation is explained

by factors not included in the regression model.

The second regression model, with the dependent variable ETR2, has a better insight into

the influence factors. Variable coefficients IPC, inflation rate, ROE, ROA, leverage (for a

significance level of 10%) and inventory intensity are significant and have a positive correlation

with the dependent variable. The Year dummy variable has a negative and significant correlation

with the effective tax rate, meaning that when tax reform has been caught flat tax decrease in the

economic, effective tax rate decreased. The number of employees has a significant impact on the

dependent variable showing a significant negative correlation, an increase in the number of

employees involves a decrease in the effective tax rate.

Variable Coefficient Std. Error t-Statistic Prob. Variable Coefficient Std. Error t-Statistic Prob.

C 0.184836 0.104409 1.770301 0.0771 C -0.01989 0.006631 -2.99935 0.0028

IPC -0.008203 0.027602 -0.297178 0.7664 IPC 0.004326 0.001753 2.468311 0.0138

INFL 0.288385 0.079269 3.63807 0.0003 INFL 0.037703 0.005071 7.434737 0

YEAR -0.038152 0.028573 -1.335243 0.1822 YEAR -0.003865 0.001818 -2.125221 0.0339

ROA? 0.094725 0.12269 0.772069 0.4403 ROA? 0.066221 0.007794 8.496892 0

ROE? 0.028938 0.0157 1.843161 0.0657 ROE? 0.002466 0.000996 2.476273 0.0135

LEVIER? 0.004071 0.001949 2.088955 0.0371 LEVIER? 0.000238 0.000124 1.927787 0.0543

INVINT? 0.521589 0.081845 6.372906 0 INVINT? 0.08711 0.005192 16.77803 0

CINT? -0.000777 0.013555 -0.057334 0.9543 CINT? -0.001139 0.00086 -1.325146 0.1855

SALARIATI? -6.37E-07 3.75E-06 -0.169703 0.8653 SALARIATI? -5.36E-07 2.38E-07 -2.250229 0.0247

RATA_IND? -0.00263 0.000716 -3.673286 0.0003 RATA_IND? 3.81E-05 4.55E-05 0.83739 0.4026

R-squared 0.207714 0.19145 R-squared 0.554465 0.016644

Adjusted R-squared 0.131076 0.294452 Adjusted R-squared 0.511191 0.024903

S.E. of regression 0.274477 0.337185 S.E. of regression 0.017411 -5.178077

Sum squared resid 55.29773 0.756329 Sum squared resid 0.22159 -4.757702

Log likelihood -63.88562 0.498145 Log likelihood 2150.998 -5.016616

F-statistic 2.710333 2.062552 F-statistic 12.813 1.250418

Prob(F-statistic) 0 Prob(F-statistic) 0

Durbin-Watson stat Durbin-Watson stat

Akaike info criterion Akaike info criterion

Schwarz criterion Schwarz criterion

Hannan-Quinn criter. Hannan-Quinn criter.

Total pool (balanced) observations: 806 Total pool (unbalanced) observations: 803

Mean dependent var Mean dependent var

S.D. dependent var S.D. dependent var

Dependent Variable: ETR1? Dependent Variable: ETR2?

Method: Pooled Least Squares Method: Pooled Least Squares

Cross-sections included: 62 Cross-sections included: 62

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The whole regression model is valid with probability zero Fisher test and the variables

included in the analysis explaines 55.44% of variation of the dependent variable.

Using logarithmical data and introducing a new variabile (SIZE), the model becomes:

The results are shown in the following table:

Alternative regression model to the basic one, with the dependent variable the effective

tax rate Etra, statistically speaking, is valid; Fisher test probability is less than the significance

level considered. The determination is 60.22% which suggests that the variation of ETRa is

explained for 60.22% by the variables included in the model, the remaining variation is

explained by other factors omitted. Variable coefficients IPC, inflation rate, YEAR, ROAL,

ROEL, CINTL, RIND, LOG_SALARIATI and SIZE are significant in statistical terms. A

positive correlation was observed between the dependent variable and INFL, ROAL, SIZE and

RIND and negative correlation was found between the effective tax rate and IPC, YEAR, ROEL,

CINTL and LOG_SALARIATI.

Serial autocorrelation hypothesis on the data, the DW statistics for the two models ETRb

and Etra and are compared with tabulated DW for the 5% significance level, a sample of 667

observations and 11 coefficients. The table dU is 1.83997 and DL=1.90244, DW for regression

Variable Coefficient Std. Error t-Statistic Prob. Variable Coefficient Std. Error t-Statistic Prob.

C -0.962424 0.360702 -2.668197 0.0078 C -0.63808 0.270284 -2.360772 0.0186

IPC -0.010285 0.002739 -3.755082 0.0002 IPC -0.007278 0.002052 -3.546315 0.0004

INFL 0.101054 0.01176 8.592695 0 INFL 0.075317 0.008812 8.546647 0

YEAR -0.006005 0.002458 -2.443354 0.0148 YEAR -0.00517 0.001842 -2.807007 0.0052

ROAL? 2.605393 0.815092 3.196439 0.0015 ROAL? 1.847949 0.610772 3.025595 0.0026

ROEL? -1.64205 0.413125 -3.974706 0.0001 ROEL? -1.161511 0.309566 -3.75206 0.0002

LEVERAGE? -0.035257 0.043868 -0.803721 0.4219 LEVERAGE? -0.016859 0.032871 -0.512869 0.6082

INVINTL? -0.075851 0.070092 -1.082171 0.2796 INVINTL? -0.064533 0.052522 -1.228699 0.2197

CINTL? -0.367466 0.143166 -2.566712 0.0105 CINTL? -0.315731 0.107278 -2.943102 0.0034

RIND? 2.675767 0.702984 3.806297 0.0002 RIND? 1.857684 0.526766 3.526581 0.0005

LOG_SALARIATI? -0.004796 0.002157 -2.224093 0.0265 LOG_SALARIATI? -0.003493 0.001616 -2.161286 0.0311

SIZE? 0.013352 0.002456 5.436435 0 SIZE? 0.009447 0.00184 5.132854 0

R-squared 0.602221 0.023666 R-squared 0.575796 0.018882

Adjusted R-squared 0.554006 0.032754 Adjusted R-squared 0.524377 0.023766

S.E. of regression 0.021874 -4.704083 S.E. of regression 0.016391 -5.281238

Sum squared resid 0.284205 -4.211273 Sum squared resid 0.159579 -4.788429

Log likelihood 1641.812 -4.513159 Log likelihood 1834.293 -5.090314

F-statistic 12.49018 1.306202 F-statistic 11.19819 1.288366

Prob(F-statistic) 0 Prob(F-statistic) 0

Hannan-Quinn criter. Hannan-Quinn criter.

Durbin-Watson stat Durbin-Watson stat

S.D. dependent var S.D. dependent var

Akaike info criterion Akaike info criterion

Schwarz criterion Schwarz criterion

Included observations: 13 Included observations: 13

Cross-sections included: 62 Cross-sections included: 62

Mean dependent var Mean dependent var

Dependent Variable: ETRA? Dependent Variable: ETRB?

Method: Pooled Least Squares Method: Pooled Least Squares

Sample: 1999 2011 Sample: 1999 2011

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Etra has the value 1.30, and for ETRb is 1.28, both being within the range of values between 0

and dL, signifying the presence of serial autocorrelation of the residues in both regression

models.

Conclusions

In this paper I studied the determinants of effective tax rate. The period of analysis was

1999-2011; the database consisted of financial statements of companies listed on the Bucharest

Stock Exchange, companies which are classified into 11 sectors.

Aim of the study was to determine the effective tax rate, presenting professional articles

on national and international. Case studies focused on the issue of ETR concept approach include

the period 1997 to 2012, and could easily see the evolution of thought in the literature on

calculation of the effective tax rate and its determinants.

In the period under review, the following conclusions can be derived regarding the

evolution of effective tax rate:

• At the aggregate level of the analyzed companies, the highest values of average

effective tax rates were recorded in 1999, the average effective tax rate ETR1 in value of

37.15%, while ETR2 was worth 3, 33%. Also, during the period 1999-2005, ETR1 was lower

than statutory rate, followed in 2005-2006 to record values exceeding the statutory rate, returning

to initial trend after 2007. Regarding effective tax rate ETR2, we see recorded values below the

statutory rate for the full analysis.

• The analysis of the sector in the period under review, we conclude that the sectors most

affected by the tax are: transport and storage, construction, while the least affected sectors are

tourism, energy. Also, the economic crisis has affected all sectors of Romania, the impact being

in the poor financial statements resulting in a high effective tax rates.

For the econometric analysis, I proposed two types of regression models with dependent

variable as the effective tax rate calculated in the two ways mentioned in the above lines. The

first version of the model involving econometric analysis using data imported from Excel

directly, without applying the natural logarithm operations. As independent variables I chose as

significant macroeconomic variables (Corruption Perception Index, rate of inflation, and the

inclusion of a dummy variable to capture the impact of the type of tax reform in Romania) and

company-specific variables (ROA, ROE, leverage, number of employees, the rate of

indebtedness, inventory and capital intensity). Including these variables aimed to determine the

factors influencing, the choice being made in the other models presented in the literature. This

did not include influences conclusive unless ETR2 model.

In further study, I chose the realization of two models, this time I created a new series of

variables applying the natural logarithm operator. Also, in the model I included a new variable to

measure company size, SIZE, defined as the natural logarithm of turnover. There weren’t large

differences between the new models ETRb and Etra, influences of the variables having the same

meaning in both cases. Obtained differences can be explained by different methods of calculation

of the dependent variable.

Thus, I can deduce:

• The coefficients of IPC, INFL, YEAR, ROAL, ROEL, CINTL, RIND,

LOG_SALARIATI and SIZE are significant in statistical terms;

• Positive correlation was observed between the dependent variable and INFL, ROAL,

SIZE and RIND;

• Negative correlation was found between the effective tax rate and IPC, YEAR, ROEL,

CINT and LOG_SALARIATI.

12

The aim of this analysis is determinate the factors influencing the effective tax burden of

the economic agent. Based on the results, we can provide valuable information in order to

improve fiscal and financial management of a company.

Taking into account the conclusions, the company, in order to reduce the effective rate of

tax, may adjust its specific indicators by increasing or reducing. Also, depending on economic

conditions existing at a given time, and the characteristics of the industry and the interests of the

company, it can approach a mixed policy by reducing the effective tax rate while maintaining its

funding and financial policy, maximizing their performance and tracking the goals imposed by

financial management.

The analysis in this paper has certain limitations on the availability of financial data for

Romania. Another limitation of the study is the proposed estimation method (OLS - the method

of least squares) and non-availability to use of other methods due of computer program Eviews.

Method of data approach in EViews is data-pool type, which have characteristics and hence

statistical tests are lower compared to a simple regression. Also a factor is the failure of all OLS

assumptions.

13

References

1. Boudewijn Janssen, 2005, „Corporate effective tax rates in the NETHERLANDS”,

Netherlands Economic Review, Nr 1;

2. Boudewijn Janssen, Willem Buijink, 2000, „Determinants of the Variability of Corporate

Effective Tax Rates (ETRs): Evidence for the Netherlands”, MARC Working Paper

MARC-WP/3/2000-08;

3. Codirlaşu, A., 2007, „Econometrie aplicatăutilizând EViews 5.1”, note de curs,

Programul de Master Specializat Managementul Sistemelor Bancare, ASE Bucureşti;

4. Crabbé Karen, Lessius, K.U.Leuven, 2010, „The impact of the auditor and tax advice on

the effective tax rate” ,Katholieke Universiteit Leuven , Belgia;

5. Gupta Sanjay, Newbery Kaye, 1997, „Determinants of the variability in corporate

effective tax rates: Evidence from longitudinal data”, Journal of Accounting and Public

Policy;

6. Kim Kenneth A., Limpaphayom Piman, 1998, „Taxes and firm size in pacific-basin

emerging economies”, Journal of International Accounting, Auditing & Taxation,

7(1):47-68;

7. Lee Namryoung, Swenson Charles, 2012, „Are Multinational Corporate Tax Rules as

Important as Tax Rates?”, The International Journal of Accounting 47, p. 155–167;

8. Lazăr Sebastian, 2010a, „EFFECTIVE CORPORATE INCOME TAX RATE IN

ROMANIA: A MICROBACKWARD LOOKING APPROACH”, University “Al. I.

Cuza” of Iasi, Romania;

9. Lanis Roman, Richardson Grant, 2007, „Determinants of the variability in corporate

effective tax rates and tax reform: Evidence from Australia”, Journal of Accounting and

Public Policy 26 p 689–704;

10. Necula Ciprian, 2012, „Econometrie – nivel de complexitate”, suport de curs;

11. Necula Ciprian, 2010, „Bazele econometriei”, note de curs, Master DOFIN

12. Startz Richard, 2013, „ EViews Illustrated for Version 8”, University of California, Santa

Barbara;

13. Spircu Liliana, 2012, „Econometrie aplicată în finanțe”, note de curs, Academia de Studii

Economice București, Facultatea de Finante, Asigurări, Bănci și Burse de Valori

București, Master Finanțe Corporative;

14. Radu Stroe, Dan Armeanu, 2004, „Finante”, Editura ASE, Biblioteca digitala ASE;

15. Ristea Mihai, Dumitru Corina-Graziella, 2005, „Contabilitate financiara”, ed.

Universitara, Biblioteca Digitala ASE;

16. Vintilă Georgeta, 2012a, „Mangementul fiscal al întreprinderii”, Academia de Studii

Economice : Facultatea de Finanțe, Asigurări, Bănci și Burse de Valori : Maste –

Management financiar și Bursier, Bucureşti;

17. Vintilă Georgeta, Armeanu Ștefan Daniel, Filipescu Maria-Oana, Moscalu Maricica,

Lazăr Paula, 2012b, „Studiu privind corelaţia politică fiscală – responsabilitate socială

corporativă” : Economie teoretică şi aplicată, Volumul XIX, No. 4(569), p. 3-14;

14

18. International Accounting Standard 12 : Income Taxes;

19. http://ro.wikipedia.org/wiki/Construc%C8%9Biile_%C3%AEn_Rom%C3%A2nia;

20. www.firme.info;

21. www.ktd.ro;

22. www.bvb.ro;

23. www.worldbank.org;

24. www.transparency.org.ro;

25. www.mfinante.ro;

26. www.insse.ro/cms/rw/pages/index.ro.do;

27. http://www.stanford.edu/~clint/bench/dw05d.htm;

28. http://ro.wikipedia.org/wiki/Industria_Rom%C3%A2niei.

15

Appendix

Tabel 1 : Evolution of EATR1 și EATR2 in Romania

Anul Sector de activitate EATR1 EATR2 Cota de impozit legală

1999 Total 0.371564639 0.03382885 0.38

1999 Comert 0.376256255 0.048521033 0.38

1999 Constructii 0.50257252 0.020549792 0.38

1999 Farmaceutic 0.415719905 0.043269233 0.38

1999 Industrie prelucrătoare 0.396177138 0.03515129 0.38

1999 Mase plastice 0.448582745 0.037399453 0.38

1999 Masini și utilaje 0.248055307 0.035497407 0.38

1999 Metalurgie 0.142801301 0.024491061 0.38

1999 Produse alimentare 0.326012171 0.03104884 0.38

1999 Produse chimice 0.350277581 0.038678879 0.38

1999 Resurse energetice 0.386073923 0.012460481 0.38

1999 Transport și depozitare 0.548857106 0.08531832 0.38

1999 Turism 0.123067068 0.009769081 0.38

2000 Total 0.225698505 0.025132004 0.25

2000 Comert 0.172171838 0.077658238 0.25

2000 Constructii 0.353233935 0.016522248 0.25

2000 Farmaceutic 0.173340765 0.040238647 0.25


2000 Mase plastice 0.25928129 0.022595931 0.25


2000 Metalurgie 0.038796402 0.008629272 0.25


2000 Produse chimice 0.180172247 0.023999801 0.25



2000 Turism 0.116263252 0.005296344 0.25

2001 Total 0.164378233 0.020879248 0.25

2001 Comert 0.153145127 0.044882189 0.25

2001 Constructii 0.201400941 0.013271938 0.25

2001 Farmaceutic 0.203698741 0.037747195 0.25


2001 Mase plastice 0.203784845 0.017741815 0.25


2001 Metalurgie 0.040143052 0.007552618 0.25


2001 Produse chimice 0.065926028 0.010630425 0.25

2001 Resurse energetice -0.179024552 0.020379144 0.25


2001 Turism 0.072484148 0.008562615 0.25

16


2002 Total 0.201671101 0.016402463 0.25

2002 Comert 0.166948078 0.018635126 0.25

2002 Constructii 0.330727604 0.016190301 0.25

2002 Farmaceutic 0.220940788 0.035571074 0.25


2002 Mase plastice 0.16181321 0.021415979 0.25


2002 Metalurgie 0.057091807 0.005614399 0.25


2002 Produse chimice 0.055239255 0.004631495 0.25



2002 Turism 0.115778634 0.005666148 0.25

2003 Total 0.245676709 0.017492639 0.25

2003 Comert 0.267303348 0.02664694 0.25

2003 Constructii 0.332544818 0.016061594 0.25

2003 Farmaceutic 0.24713859 0.03889562 0.25


2003 Mase plastice 0.16234288 0.01770955 0.25


2003 Metalurgie 0.051334459 0.007555916 0.25


2003 Produse chimice 0.05305448 0.003551479 0.25



2003 Turism 0.145702928 0.005509338 0.25

2004 Total 0.184511155 0.018411327 0.25

2004 Comert 0.283433179 0.025778014 0.25

2004 Constructii 0.204633637 0.019074852 0.25

2004 Farmaceutic 0.216195127 0.025622288 0.25


2004 Mase plastice 0.224559588 0.023631221 0.25

2004 Masini și utilaje -0.065415914 0.011383387 0.25

2004 Metalurgie 0.126926196 0.011628674 0.25


2004 Produse chimice 0.163457573 0.010209507 0.25



2004 Turism 0.117724127 0.011190636 0.25

17


2005 Total 0.174577918 0.012339756 0.16

2005 Comert 0.22068537 0.02605024 0.16

2005 Constructii 0.169579958 0.012713388 0.16

2005 Farmaceutic 0.214244636 0.020998997 0.16


2005 Mase plastice 0.157095508 0.017099715 0.16


2005 Metalurgie 0.252226133 0.013138934 0.16


2005 Produse chimice -0.016998657 0.002455586 0.16



2005 Turism 0.083449117 0.016725782 0.16

2006 Total 0.208582183 0.012250546 0.16

2006 Comert 0.183889978 0.014170631 0.16

2006 Constructii 0.191172402 0.013029604 0.16

2006 Farmaceutic 0.236496072 0.036569855 0.16


2006 Mase plastice 0.159535231 0.014655989 0.16


2006 Metalurgie 0.058966957 0.01241572 0.16


2006 Produse chimice 0 0 0.16



2006 Turism 0.070090484 0.013768688 0.16

2007 Total 0.145589032 0.01168986 0.16

2007 Comert 0.119478439 0.027668425 0.16

2007 Constructii 0.156493654 0.015740111 0.16

2007 Farmaceutic 0.29937427 0.021381037 0.16


2007 Mase plastice 0.031789405 0.004626942 0.16


2007 Metalurgie 0.054290674 0.013831685 0.16


2007 Produse chimice 0.022275338 0.000859853 0.16



2007 Turism 0.074827901 0.014167717 0.16

18


2008 Total 0.143717065 0.010011083 0.16

2008 Comert 0.122998815 0.014975942 0.16

2008 Constructii 0.198537989 0.014653195 0.16

2008 Farmaceutic 0.077390436 0.020485879 0.16


2008 Mase plastice 0.035452524 0.004331279 0.16


2008 Metalurgie 0.080682152 0.012003016 0.16


2008 Produse chimice 0.178319168 0.001637553 0.16



2008 Turism 0.079397735 0.0150167 0.16

2009 Total 0.12049623 0.016668617 0.16

2009 Comert 0.128183069 0.017890406 0.16

2009 Constructii 0.23298991 0.008062309 0.16

2009 Farmaceutic -0.62740187 0.018935532 0.16


2009 Mase plastice 0.011342143 0.000723178 0.16


2009 Metalurgie -0.005659868 0.002311122 0.16


2009 Produse chimice 0.21849547 0.002567013 0.16



2009 Turism 0.148722568 0.040542346 0.16

2010 Total 0.141404917 0.010459733 0.16

2010 Comert 0.135484175 0.013825232 0.16

2010 Constructii 0.091556019 0.009341663 0.16

2010 Farmaceutic 0.245340609 0.028829883 0.16


2010 Mase plastice -0.008041531 0.000329606 0.16


2010 Metalurgie 0.056350335 0.006143727 0.16

2010 Produse alimentare -0.099093546 0.008099584 0.16

2010 Produse chimice 0.389815677 0.002828103 0.16



2010 Turism 0.177171213 0.030688537 0.16

19


2011 Total 0.160988498 0.010002569 0.16

2011 Comert 0.143279766 0.01600841 0.16

2011 Constructii 0.245521906 0.004896683 0.16

2011 Farmaceutic 0.216781234 0.025085659 0.16


2011 Mase plastice 0.008554851 0.000222514 0.16


2011 Metalurgie 0.061712286 0.00771426 0.16


2011 Produse chimice 0 0 0.16



2011 Turism 0.171723319 0.029816337 0.16

20

Tabel 2 : Basic model ETR1

Dependent Variable: ETR1?

Method: Pooled Least Squares

Date: 06/01/13 Time: 19:31

Sample: 1999 2011

Included observations: 13

Cross-sections included: 62

Total pool (balanced) observations: 806 Variable Coefficient Std. Error t-Statistic Prob. C 0.184836 0.104409 1.770301 0.0771

IPC -0.008203 0.027602 -0.297178 0.7664

INFL 0.288385 0.079269 3.638070 0.0003

YEAR -0.038152 0.028573 -1.335243 0.1822

ROA? 0.094725 0.122690 0.772069 0.4403

ROE? 0.028938 0.015700 1.843161 0.0657

LEVIER? 0.004071 0.001949 2.088955 0.0371

INVINT? 0.521589 0.081845 6.372906 0.0000

CINT? -0.000777 0.013555 -0.057334 0.9543

SALARIATI? -6.37E-07 3.75E-06 -0.169703 0.8653

RATA_IND? -0.002630 0.000716 -3.673286 0.0003

Fixed Effects (Cross)

_ARS--C -0.058257

_ALR--C -0.023466

_ALT--C -0.028456

_ALU--C -0.096381

_AMO--C -0.026235

_ATB--C 0.009076

_ARM--C -0.024694

_ARTE--C -0.088580

_BRM--C -0.033005

_BIO--C 0.056179

_SPCU--C -0.146185

_CAOR--C -0.056200

_CBC--C -0.103784

_BCM--C 0.028804

_CEON--C 0.141484

_CMCM--C 0.007050

_CMF--C -0.031532

_CMP--C 0.001277

_COMI--C 0.012730

_CNTE--C 0.181514

_CGC--C -0.058503

_DAFR--C 0.152785

_ELJ--C 0.049413

_ELGS--C -0.152553

_ECT--C 0.035018

_ELMA--C 0.084851

_EPT--C -0.054866

_ENP--C 0.006221

_RMAH--C 0.097830

_MECF--C -0.038526

_COS--C 0.313667

_MEF--C -0.168021

_MJM--C 0.003289

21

_OIL--C -0.102683

_OLT--C 0.048209

_PEI--C -0.035831

_SNP--C 0.207473

_PREH--C 0.106070

_PPL--C -0.104292

_RTRA--C -0.084779

_ROCE--C 0.010753

_RRC--C 0.006350

_PTR--C 0.089691

_RPH--C -0.083593

_SNO--C 0.039663

_COFI--C -0.058433

_STZ--C 0.019758

_SRT--C -0.208466

_SOCP--C -0.075963

_STIB--C 0.108094

_TRP--C 0.013214

_MPN--C 0.142112

_ART--C -0.050706

_COTR--C 0.024381

_TBM--C 0.018930

_TUFE--C -0.084360

_UAM--C -0.051408

_UZT--C 0.011341

_APC--C 0.302414

_VESY--C -0.191520

_VNC--C -0.010422

_SCD--C 0.002057 Effects Specification Cross-section fixed (dummy variables) R-squared 0.207714 Mean dependent var 0.191450

Adjusted R-squared 0.131076 S.D. dependent var 0.294452

S.E. of regression 0.274477 Akaike info criterion 0.337185

Sum squared resid 55.29773 Schwarz criterion 0.756329

Log likelihood -63.88562 Hannan-Quinn criter. 0.498145

F-statistic 2.710333 Durbin-Watson stat 2.062552

Prob(F-statistic) 0.000000

22

Tabelul 3 : Basic model ETR2



Date: 06/01/13 Time: 19:44

Sample: 1999 2011



Total pool (unbalanced) observations: 803 Variable Coefficient Std. Error t-Statistic Prob. C -0.019890 0.006631 -2.999350 0.0028

IPC 0.004326 0.001753 2.468311 0.0138

INFL 0.037703 0.005071 7.434737 0.0000

YEAR -0.003865 0.001818 -2.125221 0.0339

ROA? 0.066221 0.007794 8.496892 0.0000

ROE? 0.002466 0.000996 2.476273 0.0135

LEVIER? 0.000238 0.000124 1.927787 0.0543

INVINT? 0.087110 0.005192 16.77803 0.0000

CINT? -0.001139 0.000860 -1.325146 0.1855

SALARIATI? -5.36E-07 2.38E-07 -2.250229 0.0247

RATA_IND? 3.81E-05 4.55E-05 0.837390 0.4026


_ARS--C 0.002643

_ALR--C -0.008715

_ALT--C -0.012125

_ALU--C -0.009171

_AMO--C 0.001423

_ATB--C 7.69E-05

_ARM--C -0.002825

_ARTE--C -0.015967

_BRM--C -0.017980

_BIO--C 0.011176

_SPCU--C 0.013116

_CAOR--C 0.035769

_CBC--C -0.006172

_BCM--C 0.050861

_CEON--C -0.002416

_CMCM--C 0.007808

_CMF--C -0.004133

_CMP--C 0.008582

_COMI--C -0.019888

_CNTE--C -0.001079

_CGC--C 0.014780

_DAFR--C -0.001842

_ELJ--C 0.004011

_ELGS--C -0.012320

_ECT--C 0.008656

_ELMA--C -0.006389

_EPT--C 0.005934

_ENP--C -0.028168

_RMAH--C 0.000747

_MECF--C 0.009224

_COS--C -0.015751

_MEF--C 0.000816

_MJM--C -0.012204

23

_OIL--C -0.009465

_OLT--C -0.000687

_PEI--C -0.009001

_SNP--C 0.014294

_PREH--C -0.005985

_PPL--C -0.007614

_RTRA--C -0.006877

_ROCE--C 0.003303

_RRC--C 0.021472

_PTR--C -0.012345

_RPH--C -0.012772

_SNO--C -0.014253

_COFI--C -0.007787

_STZ--C -0.008842

_SRT--C 0.027064

_SOCP--C -0.008333

_STIB--C 0.039482

_TRP--C 0.032692

_MPN--C -0.004951

_ART--C -0.007232

_COTR--C 0.002078

_TBM--C 0.008774

_TUFE--C -0.001418

_UAM--C -0.004972

_UZT--C 0.018884

_APC--C -0.014520

_VESY--C -0.013306

_VNC--C -0.013556

_SCD--C 0.000425 Effects Specification Cross-section fixed (dummy variables) R-squared 0.554465 Mean dependent var 0.016644


S.E. of regression 0.017411 Akaike info criterion -5.178077

Sum squared resid 0.221590 Schwarz criterion -4.757702

Log likelihood 2150.998 Hannan-Quinn criter. -5.016616



24

Tabel 4 : Redundant Fixed Effects Tests, basic model ETR1

Redundant Fixed Effects Tests

Pool: POOL01

Test cross-section fixed effects Effects Test Statistic d.f. Prob. Cross-section F 1.748149 (61,734) 0.0006

Cross-section Chi-square 109.334719 61 0.0001

Cross-section fixed effects test equation:


Method: Panel Least Squares

Date: 06/01/13 Time: 20:02

Sample: 1999 2011



Total pool (balanced) observations: 806 Variable Coefficient Std. Error t-Statistic Prob. C 0.184871 0.101817 1.815718 0.0698

IPC -0.005946 0.028094 -0.211636 0.8324

INFL 0.287109 0.080257 3.577379 0.0004

YEAR -0.037552 0.029343 -1.279745 0.2010

ROA? 0.110437 0.105700 1.044815 0.2964

ROE? 0.033529 0.015327 2.187584 0.0290

LEVIER? 0.003991 0.001923 2.075146 0.0383

INVINT? 0.442177 0.069585 6.354473 0.0000

CINT? -0.009898 0.009415 -1.051233 0.2935

SALARIATI? 8.34E-07 1.51E-06 0.552560 0.5807

RATA_IND? -0.002074 0.000482 -4.306230 0.0000 R-squared 0.092610 Mean dependent var 0.191450


S.E. of regression 0.282245 Akaike info criterion 0.321471

Sum squared resid 63.33150 Schwarz criterion 0.385507

Log likelihood -118.5530 Hannan-Quinn criter. 0.346062



25

Tabel 5 : Redundant Fixed Effects Tests, basic model ETR2


Pool: POOL01






Date: 06/01/13 Time: 20:01

Sample: 1999 2011




IPC 0.004685 0.002036 2.301169 0.0216

INFL 0.037329 0.005853 6.377907 0.0000

YEAR -0.004317 0.002131 -2.025889 0.0431

ROA? 0.079731 0.007680 10.38192 0.0000

ROE? 0.002849 0.001110 2.567559 0.0104

LEVIER? 0.000289 0.000139 2.072183 0.0386

INVINT? 0.060940 0.005041 12.08805 0.0000

CINT? -0.001401 0.000682 -2.055750 0.0401

SALARIATI? 1.02E-07 1.09E-07 0.935607 0.3498

RATA_IND? -0.000166 3.51E-05 -4.742301 0.0000 R-squared 0.335247 Mean dependent var 0.016644







26

Tabel 6 : Wald test results, basic model ETR1

Wald Test:

Pool: POOL01 Test Statistic Value df Probability t-statistic 0.564974 734 0.5723

F-statistic 0.319196 (1, 734) 0.5723

Chi-square 0.319196 1 0.5721

Null Hypothesis: -1 + C(1) + C(2) + C(3) + C(4) + C(5) + C(6)

+ C(7) + C(8) + C(9) + C(10) =0

Null Hypothesis Summary: Normalized Restriction (= 0) Value Std. Err. -1 + C(1) + C(2) + C(3) + C(4) +

C(5) + C(6) + C(7) + C(8) + C(9) + C(10) 0.075411 0.133477

Restrictions are linear in coefficients.

Tabel 7 : Wald test results, basic model ETR2

Wald Test:

Pool: POOL01 Test Statistic Value df Probability t-statistic -97.63390 731 0.0000

F-statistic 9532.379 (1, 731) 0.0000

Chi-square 9532.379 1 0.0000


+ C(7) + C(8) + C(9) + C(10)=0


C(5) + C(6) + C(7) + C(8) + C(9) + C(10) -0.826831 0.008469


27

Tabel 8 : Model ETRa

Dependent Variable: ETRA?


Date: 06/01/13 Time: 20:18

Sample: 1999 2011




IPC -0.010285 0.002739 -3.755082 0.0002

INFL 0.101054 0.011760 8.592695 0.0000

YEAR -0.006005 0.002458 -2.443354 0.0148

ROAL? 2.605393 0.815092 3.196439 0.0015

ROEL? -1.642050 0.413125 -3.974706 0.0001

LEVERAGE? -0.035257 0.043868 -0.803721 0.4219

INVINTL? -0.075851 0.070092 -1.082171 0.2796

CINTL? -0.367466 0.143166 -2.566712 0.0105

RIND? 2.675767 0.702984 3.806297 0.0002

LOG_SALARIATI? -0.004796 0.002157 -2.224093 0.0265

SIZE? 0.013352 0.002456 5.436435 0.0000


_ARS--C -0.019720

_ALR--C -0.020262

_ALT--C 0.008504

_ALU--C -0.031082

_AMO--C -0.001281

_ATB--C 0.007226

_ARM--C 0.002162

_ARTE--C -0.034265

_BRM--C -0.014168

_BIO--C -0.007994

_SPCU--C 0.005132

_CAOR--C 0.008647

_CBC--C 0.019240

_BCM--C 0.031581

_CEON--C 0.013760

_CMCM--C 0.022213

_CMF--C -0.004684

_CMP--C 0.007127

_COMI--C -0.007872

_CNTE--C -0.003302

_CGC--C 0.036691

_DAFR--C 0.002535

_ELJ--C -0.000464

_ELGS--C -0.053587

_ECT--C 0.014984

_ELMA--C -0.011462

_EPT--C 0.020159

_ENP--C 0.026075

_RMAH--C 0.000817

_MECF--C -0.007105

_COS--C 0.012116

_MEF--C 0.039685

28

_MJM--C 0.027089

_OIL--C 0.009289

_OLT--C -0.000359

_PEI--C -0.013385

_SNP--C 0.006491

_PREH--C -0.042950

_PPL--C -0.022785

_RTRA--C -0.002762

_ROCE--C -0.002737

_RRC--C 0.015130

_PTR--C -0.023474

_RPH--C -0.006783

_SNO--C -0.014053

_COFI--C -0.067886

_STZ--C 0.003027

_SRT--C -0.005847

_SOCP--C 0.004683

_STIB--C -0.038071

_TRP--C 0.006140

_MPN--C 0.005749

_ART--C -0.007225

_COTR--C -0.008760

_TBM--C 0.011852

_TUFE--C 0.004879

_UAM--C 0.007671

_UZT--C 0.009375

_APC--C -0.002767

_VESY--C 0.003762

_VNC--C -0.004497

_SCD--C -0.004414 Effects Specification Cross-section fixed (dummy variables) R-squared 0.602221 Mean dependent var 0.023666







29

Tabel 9 : Model ETRb

Dependent Variable: ETRB?


Date: 06/01/13 Time: 20:20

Sample: 1999 2011




IPC -0.007278 0.002052 -3.546315 0.0004

INFL 0.075317 0.008812 8.546647 0.0000

YEAR -0.005170 0.001842 -2.807007 0.0052

ROAL? 1.847949 0.610772 3.025595 0.0026

ROEL? -1.161511 0.309566 -3.752060 0.0002

LEVERAGE? -0.016859 0.032871 -0.512869 0.6082

INVINTL? -0.064533 0.052522 -1.228699 0.2197

CINTL? -0.315731 0.107278 -2.943102 0.0034

RIND? 1.857684 0.526766 3.526581 0.0005

LOG_SALARIATI? -0.003493 0.001616 -2.161286 0.0311

SIZE? 0.009447 0.001840 5.132854 0.0000


_ARS--C -0.013777

_ALR--C -0.015339

_ALT--C 0.005057

_ALU--C -0.023404

_AMO--C -0.000946

_ATB--C 0.006699

_ARM--C 0.001289

_ARTE--C -0.024486

_BRM--C -0.010518

_BIO--C -0.005360

_SPCU--C 0.003655

_CAOR--C 0.006278

_CBC--C 0.014455

_BCM--C 0.024020

_CEON--C 0.012216

_CMCM--C 0.016665

_CMF--C -0.003415

_CMP--C 0.005340

_COMI--C -0.006316

_CNTE--C -0.001141

_CGC--C 0.025579

_DAFR--C 0.001892

_ELJ--C -0.000489

_ELGS--C -0.039704

_ECT--C 0.012314

_ELMA--C -0.008780

_EPT--C 0.016159

_ENP--C 0.016732

_RMAH--C 0.001161

_MECF--C -0.005054

_COS--C 0.002831

_MEF--C 0.037559

30

_MJM--C 0.021002

_OIL--C 0.007128

_OLT--C 0.000550

_PEI--C -0.009980

_SNP--C 0.006362

_PREH--C -0.030782

_PPL--C -0.017650

_RTRA--C -0.002681

_ROCE--C -0.001410

_RRC--C 0.012320

_PTR--C -0.018732

_RPH--C -0.005264

_SNO--C -0.011851

_COFI--C -0.049416

_STZ--C 0.001072

_SRT--C -0.003328

_SOCP--C 0.002812

_STIB--C -0.025365

_TRP--C 0.004900

_MPN--C 0.003280

_ART--C -0.006262

_COTR--C -0.005737

_TBM--C 0.008727

_TUFE--C 0.004318

_UAM--C 0.005131

_UZT--C 0.007159

_APC--C -0.002272

_VESY--C 0.003624

_VNC--C -0.003954

_SCD--C -0.003623 Effects Specification Cross-section fixed (dummy variables) R-squared 0.575796 Mean dependent var 0.018882







31

Tabel 10 : Redundant Fixed Effects Tests, model ETRa


Pool: POOL01




Dependent Variable: ETRA?


Date: 06/01/13 Time: 20:51

Sample: 1999 2011




IPC -0.005295 0.002715 -1.950523 0.0515

INFL 0.060150 0.008881 6.772685 0.0000

YEAR -0.005509 0.002638 -2.088788 0.0371

ROAL? 3.688711 0.750712 4.913617 0.0000

ROEL? -2.137768 0.380751 -5.614608 0.0000

LEVERAGE? -0.028558 0.039896 -0.715804 0.4744

INVINTL? -0.062723 0.045361 -1.382771 0.1672

CINTL? -0.339943 0.105599 -3.219176 0.0013

RIND? 3.440878 0.649740 5.295780 0.0000

LOG_SALARIATI? -0.001617 0.001287 -1.256932 0.2092

SIZE? 0.002038 0.001210 1.685174 0.0924 R-squared 0.484106 Mean dependent var 0.023666







32

Tabel 11 : Redundant Fixed Effects Tests, model ETRb


Pool: POOL01




Dependent Variable: ETRB?


Date: 06/01/13 Time: 20:53

Sample: 1999 2011




IPC -0.003795 0.002042 -1.858271 0.0636

INFL 0.047350 0.006682 7.086345 0.0000

YEAR -0.004832 0.001984 -2.435077 0.0152

ROAL? 2.533010 0.564807 4.484738 0.0000

ROEL? -1.467515 0.286462 -5.122888 0.0000

LEVERAGE? -0.016834 0.030016 -0.560811 0.5751

INVINTL? -0.054167 0.034128 -1.587177 0.1130

CINTL? -0.267172 0.079449 -3.362818 0.0008

RIND? 2.330103 0.488839 4.766607 0.0000

LOG_SALARIATI? -0.001141 0.000968 -1.178425 0.2391

SIZE? 0.001481 0.000910 1.627056 0.1042 R-squared 0.445372 Mean dependent var 0.018882







33

Tabel 12 : Wald test results, basic model ETRa

Wald Test:


F-statistic 2.749400 (1, 594) 0.0978

Chi-square 2.749400 1 0.0973


+ C(7) + C(8) + C(9) + C(10)+C(11)=0


C(5) + C(6) + C(7) + C(8) + C(9) + C(10) + C(11) 1.278078 0.770794


Tabel 13 : Wald test results, basic model ETRb

Wald Test:


F-statistic 0.968110 (1, 594) 0.3256

Chi-square 0.968110 1 0.3252


+ C(7) + C(8) + C(9) + C(10)+C(11)=0


C(5) + C(6) + C(7) + C(8) + C(9) + C(10) + C(11) 0.568294 0.577578


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