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208 _R._ _Murgai/ Agricultural Economics 25 (2001) 199-209_ and _au,_ respectively (i.e. _a A'= ap +a A_ and _au=_ _aM+ aL)._ As in the two-factor case, given the initial factor shares in time period 0 (1961), the factor shares (more precisely, _ap faA'_ and _aM /au)_ that would have been observed in time period _T_ (1994) in the absence of Hicks-biased technical change can be computed for different values of the elasticities of substitution.
The Divisia input index using these bias-corrected factor shares is then given by where (A.7) The TFP residual is computed by subtracting the bias-corrected growth rate of aggregate inputs (Eq. (A.6)) from the observed growth rate of the aggregate output. The sensitivity of the computed TFP growth rate to different assumptions about _CJ,_ _CJ A,_ and _CJ L_ depends on the growth rate of the fertiliser:land ratio and machines:labour ratio, and the initial shares of fertiliser and land in the total income.

**References**

Ahluwahlia, D., 1996. Agricultural growth in India: trends, sources and challenges. Manuscript. World Bank Resident Mission, New Delhi.
Alston, J.M., Norton, G.W., Pardey, P.G., 1995. Science under scarcity: principles and practice for agricultural research evaluation and priority setting. Cornell University Press, Ithaca, London.
Antle, J.M., Capalbo, S.M., 1988. An introduction to recent developments in production theory and productivity measurement. In: Capalbo, S.M., Antle, J.M. (Eds.), Agricultural Productivity: Theory and Measurement. Resources for the Future. Washington, DC.
Binswanger, H.P., 1974. The measurement of technical change biases with many factors of production. Am. Econ. Rev. 64 (6), 964-976.
Binswanger, H.P., 1978. Measured biases of technical change: the United States. In: Binswanger, H.P., Ruttan, V.W., et a!. (Eds.), Induced Innovation: Technology, Institutions, and Development.
Johns Hopkins University Press, Baltimore, MD.
Byerlee, D., 1992. Technical change, productivity and sustainability in irrigated cropping systems of South Asia: emerging issues in the post-Green Revolution Era. J. Int. Dev.
4, 477-496.
de Janvry, A., Sadoulet, E., Fafchamps, M., 1989. Agrarian structure, technological innovations and the state. In: Bardhan, P. (Ed.), The Economic Theory of Agrarian Institutions. Oxford University Press, Oxford.
Desai, B., 1994. Contribution of institutional credit, self-finance and technological change to agricultural growth in India. Indian J. Agric. Econ. 49 (3), 457-475.
Dholakia, R.M., Dholakia, B.M., 1993. Growth of total factor productivity in Indian agriculture. Indian Econ. Rev. 28 (I), 25-40.
Diamond, P., McFadden, D., Rodriguez, M., 1978. Measurement of the elasticity of factor substitution and bias of technical change.
In: Fuss, M., McFadden, D. (Eds.), Production Economics: A Dual Approach to Theory and Applications, Vol. 2.
North-Holland Press, Amsterdam.
Diewert, W.E., 1976. Exact and superlative index numbers. J.
Econometr. 4, 115-146.
Diewert, W.E., Nakamura, A.O., Sharpe, A., 1999. Introduction and overview. Canadian J. Econ. 32 (Suppl. 5), 5-15.
Evenson, R.E., Pray, C.E., Rosegrant, M.W., 1999. Agricultural research and productivity growth in India. Research Report 109, International Food Policy Research Institute.
Hayami, Y., Ruttan, V.W., 1985. Agricultural development: an international perspective. Johns Hopkins University Press, Baltimore, MD.
Hazell, P., Ramaswamy, C., 1991. The Green Revolution reconsidered: the impact of high-yielding rice varieties in South India. Johns Hopkins University Press, Baltimore, MD.
Hsieh, C.T., 1998. Measuring biased technological change.
Working Paper, Princeton University.
Kako, T., 1978. Decomposition analysis of derived demand for factor inputs: the case of rice production in Japan. Am. J. Agric.
Econ. 60, 628-635.
Kumar, P., Rosegrant, M., 1994. Productivity and sources of growth for rice in India. Econ. Pol. Weekly 29 (53), 183-188.
Murgai, R., 1997. Diversity in economic growth and technical change: a district wise disaggregation of the Punjab and Haryana growth experience. Ph.D. Dissertation, University of California, Berkeley.
Murgai, R., Ali, M., Byerlee, D., 2000. Productivity growth and sustainability in post-Green Revolution Agriculture in the Indian and Pakistan Pun jabs. World Bank Research Observer (in press).
Pingali, P.L., Heisey, P.W., 1999. Cereal crop productivity in developing countries: past trends and future prospects.
CIMMYT Economics Paper 99-03, Mexico DF, CIMMYT.
Rodrik, D., 1997. TFPG Controversies, Institutions, and Economic Performance in East Asia. NBER Working Paper 5914, Cambridge, MA.
Rosegrant, M.W., Evenson, R.E., 1993. Agricultural productivity growth in Pakistan and India: a comparative analysis. Pakistan Dev. Rev. 32 (4), 433-451.
Ruttan, V.W., Binswanger, H.P., 1978. Induced innovation and the Green Revolution. In: Binswanger, H.P., Ruttan, V.W., et a!. (Eds.), Induced Innovation: Technology, Institutions and Development. Johns Hopkins University Press, Baltimore, MD.

A dataset, survey, database, index, census, registry, or information system with a specific proper name that can be cited, queried, or downloaded as a data source

A data source described by its characteristics or producer rather than a proper name, containing a data noun and at least one identifying descriptor

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_R._ _Murgai/ Agricultural Economics 25 (2001) 199-209_ 209 Sidhu, D.S., Byerlee, D., 1992. Technical change and wheat productivity in the Indian Punjab in the post-Green Revolution period. CIMMYT Economics Paper 92-02, Mexico, DF.
Thirtle, C., 1985a. The microeconomic approach to induced innovation: a reformulation of the Hayami and Ruttan model.
Manchester Sch. Econ. Social Stud. 53 (3), 263-279.
Thirtle, C., 1985b. Induced innovation in United States field crops, 1939-1978. J. Agric. Econ. 36, 1-14.

Yeung, P., Roe, T.L., 1978. A CES test of induced technical change: Japan. In: Binswanger, H.P., Ruttan, V.W., et al.
(Eds), Induced Innovation: Technology, Institutions and Development. Johns Hopkins University Press, Baltimore, MD.
Young, A., 1995. The tyranny of numbers: confronting the statistical realities of the East Asian growth experience. Quart.
J. Econ. 110 (3), 641-680.

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Chong, Alberto; Galdo, Virgilio

**Working Paper**
## Should State-Owned Firms Change CEOs Before Privatization? The Case of the Telecommunications Industry

Working Paper, No. 481

**Provided in Cooperation with:**
Inter-American Development Bank (IDB), Washington, DC _Suggested Citation:_ Chong, Alberto; Galdo, Virgilio (2003) : Should State-Owned Firms Change CEOs Before Privatization? The Case of the Telecommunications Industry, Working Paper, No. 481, InterAmerican Development Bank, Research Department, Washington, DC This Version is available at:
[https://hdl.handle.net/10419/88052](https://hdl.handle.net/10419/88052)

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Inter-American Development Bank Banco Interamericano de Desarrollo (BID) Research Department Departamento de Investigación Working Paper #481

# Should State-Owned Firms Change CEOs Before Privatization? The Case of the Telecommunications Industry

by

### Alberto Chong Virgilio Galdo

#### Inter-American Development Bank

February 2003

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**Cataloging-in-Publication data provided by the**
**Inter-American Development Bank**
**Felipe Herrera Library**

Chong, Alberto.

Should state-owned firms change CEOs before privatization : the case of the telecommunications industry / by Alberto Chong, Virgilio Galdo.

p. cm. (Research Department Working paper series ; 481) Includes bibliographical references.

1. Telecommunication. 2. Government business enterprises.  3. Government business
enterprises--Employees. 4. Privatization. I. Galdo, Virgilio. II. Inter-American Development Bank. Research Dept. III. Title. IV. Series.

384 C889--------dc21 ©2003 Inter-American Development Bank 1300 New York Avenue, N.W.
Washington, D.C. 20577 The views and interpretations in this document are those of the authors and should not be attributed to the Inter-American Development Bank, or to any individual acting on its behalf.

The Research Department (RES) produces the Latin American Economic Policies Newsletter, as well as working papers and books, on diverse economic issues.

To obtain a complete list of RES publications, and read or download them please visit our web site at: [http://www.iadb.org/res](http://www.iadb.org/res/32.htm) 2

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**Abstract** **[*]**

Should state-owned enterprises change chief executive officer before privatizing?
We test competing views on this question by complementing a recently released database with newly collected data. We are able to cover 77 telecommunications privatizations, which account for nearly 80 percent of the sector in terms of value.
We find that CEO replacement will improve performance in the telecommunications industry before privatization as measured by penetration, operating efficiency, and profitability. CEO change before privatization does appear to have real consequences in firm performance before privatization.
Moreover, findings are consistent with previous research that links CEO replacement and an increase in privatization prices.

**JEL Classification** : G32, H10, J45, O1
**Word Count** : 2,195
**Key Words** : Privatization, Corporate Governance, Telecommunications

- Research Department, Inter-American Development Bank. Luisa Zanforlin provided comments and suggestions.
The usual disclaimer applies. The findings and interpretations of the authors do not necessarily represent the views of the Inter-American Development Bank or its executive directors. Corresponding author: Alberto Chong, Research Department, Inter-American Development Bank, Stop W-0436, 1300 New York Ave, NW, Washington, DC 20577, USA. Fax: (202) 623-2481, Tel: (202) 623-1536. E-mail: _albertoch@iadb.org_ 4

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#### **1. Introduction**

Recent research shows that the change in CEO before privatization has a bearing on privatization prices. In fact, when taking endogeneity problems into account, López-de-Silanes (1997) shows that replacing the CEO before privatization is linked with a 54 percent increase in the net privatization price in the case of Mexico. Buyers may be willing to pay higher prices for firms whose CEOs have been replaced, as profitability of the firm may have improved due to restructuring before privatization. The new owners may have to do less tweaking with the firm after privatization and may reap benefits relatively faster. This finding is particularly important as CEO replacement before privatization has become a relatively common policy issue in developing countries, and it tends to receive relatively broad political support (Chong and López de-Silanes, 2002a). Still, taking the findings by López-de-Silanes (1997) at face value, there is still some lack of understanding on the mechanisms by which CEO replacement may affect the productive process of a firm before privatization.

In this note we seek to complement the research by López-de-Silanes, by exploring the two key possible views by which replacement of top management before privatization may impact the productive process of the firm and thus increase privatization prices. The first view is that a change in CEO before privatization sends an unequivocal signal to prospective buyers on the seriousness of the privatization process. This eliminates incentives for corruption on the part of the old management that otherwise, would have tried to maximize rents before the firm is privatized. According to this signaling view, top management replacement before privatization will contribute to the increase in privatization prices once the firm is on sale, regardless of any restructuring done before privatization (Kikeri, 1999).

On the other hand, according to the restructuring view, the managers of state-owned enterprises are good in terms of political abilities but are not good at actually running firms. The current management has the wrong human capital to face competition and the new market conditions that the firm will soon face once it is privatized. A new chief executive officer, with the appropriate human capital, is thus needed in order to implement all necessary restructuring and run the firm efficiently until privatization takes place (Rosen, 1992; Barberis, Boycko, Shleifer, and Tsukanova, 1996). Thus, replacing the chief executive officer before privatization provides the firm with a step forward towards adapting the firm to the forthcoming market conditions before actual transference of ownership to private hands takes place. This, it is 6

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believed, helps smooth out the transition of the firm to a competitive market economy.

According to this view, top management replacement before privatization will yield higher privatization prices, as prospective buyers will value the restructuring done before privatization. [1] We build on a recent data set by Chong and López-de-Silanes (2002b) who collect information on privatization characteristics of state-owned enterprises for firms around the world. We focus on the sub-group of firms from the telecommunications sector. As is well known, until recently this sector has been typically considered among the “jewels” of privatization. Focusing on one single sector allows us to minimize potential problems related with industry heterogeneity. Also, the gathering of additional data necessary for this research is relatively less complicated, as several data sources are available for the case of telecommunications. We are thus able to expand the data set from Chong and López-de-Silanes and further minimize sample bias problems, if any. [2] Our paper is organized as follows. Section 2 describes the data employed. Section 3 presents our empirical findings. Finally, the last section concludes.

#### **2. Data**

Our sample is based on a data set by Chong and López-de-Silanes (2002b) who obtained information for 400 privatizations around the world for the period 1984-2000, of which around 74 were from the telecommunications sector. The sample covers about 75 percent of the privatizations carried out in the telecommunications sector in the world and account for an estimated 80 percent of the revenues brought in by privatizations in the sector worldwide during the 1990s (World Bank, 2001). [3] Furthermore, we are able to expand their sample for telecommunications firms by around five percent by using three additional sources: the firms themselves, the regulatory agencies, and the International Telecommunications Union (2002). To 1 Barberis, Boycko, Shleifer, and Tsukanova (1996) use a survey of Russian shops to measure the importance of alternative channels through which privatization promotes restructuring. While they find that the presence of new managers in privatized firms raises the likelihood of restructuring the firm after privatization, they show that keeping old managers but adding equity incentives in such firms do not promote restructuring after privatization. According to these researchers, their findings provide empirical support to the view that management replacement after privatization is crucial in the restructuring process of the firm.
2 Still, Chong and López-de-Silanes (2002b) provide evidence that their sample of firms is unbiased.
3 These researchers prepared a detailed questionnaire addressed to the CEO with a recommendation to direct it to the chief financial officer and the director of human resources of the corresponding firms. They also used additional sources extensively, in particular, documents from multilateral organizations, regulatory agencies, ministries, and international publications (Chong and López-de-Silanes, 2002b).

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survey of Russian shops
data set by Chong and López-de-Silanes

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achieve this, we followed a procedure analogous to that in Chong and López-de-Silanes (2002b).

Thus, we organized a questionnaire in two different areas. The first area covered pre privatization firm characteristics, such as sales, profits, liabilities, CEO change, and the presence of unions. The second area focused on the privatization process, and in particular, on shares sold, the type of sale, and foreign participation. The key explanatory variable of interest is a dummy variable that equals one if the firm changed CEO up to three years prior to privatization, and zero otherwise. [4] We complemented our firm-specific information with country-level macroeconomic data, mainly from the World Bank (2001) and Wallsten (2001). In particular, we used the rate of growth, the rate of inflation, the gross domestic product, and the presence of an independent regulatory agency at the time of CEO replacement, among other measuress. Additionally, we gathered information on economic performance at the firm level from Bloomberg, Economatica, Worldscope, and the International Telecommunications Union (2002). [5] Following related work on the telecommunications literature, three basic outcome measures were collected: change in telephone lines per inhabitant before and after CEO change (penetration), change in telephone lines per employee before and after CEO change (operational efficiency), and change in returns on sales before and after CEO change (profitability). Table 1 presents exact definitions of all the variables used in this paper. [6]

#### **3. Evidence**

Along the basic lines of the methodology by La Porta and López-de-Silanes (1999), Table 2 provides empirical evidence on the link between CEO change before privatization and change in economic performance after replacement. The evidence points towards a confirmation of the view that CEO replacement before privatization is associated with firm restructuring, rather than with firm signaling. Not only is the coefficient of our variable of interest positively associated with change in firm performance before privatization, but it is also statistically significant at 1 4 In fact, according to our sample, CEO change before privatization varies widely from region to region. While it has been common in Africa, Latin America, and developed countries, it has been much less used in Asia and Transition Economies.
5 Subscription-based Bloomberg, Economatica, and Worldscope deliver international financial information in a standardized format that facilitates comparisons between companies, countries, regions, and industries. Worldscope, for instance, covers approximately 90 percent of the worlds stock market value and includes records on more than 20,000 active companies representing over 50 emerging and established markets.

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percent with respect to change in penetration, and at 5 percent with respect to both change in operating efficiency and change in profitability. In fact, the results suggest that CEO change has a considerable positive impact on changes in performance, as it adds 35 percentage points to mean changes in penetration, 57 percentage points to mean changes in operating efficiency and 7 percentage points to mean changes in profitability. Interestingly, these results are stable to the inclusion of a dummy variable that accounts for the presence of an independent regulatory agency at the time of CEO replacement. The latter is also shown in Table 2.

Furthermore, according to our results, CEO replacement is the only statistically significant variable that is robustly linked with change in firm economic performance among the privatization characteristics considered in this research. In fact, while foreign participation in the privatization process yields a positive and statistically significant sign with respect to change in firm profitability, it does not have any bearing on either change in penetration or change in operating efficiency. Similar results are obtained in the case of the percentage of shares sold, as such a variable is only statistically significant when associated with change in profitability, but not when linked with change in penetration or change in operating efficiency. [7] Similarly, most of the firm characteristics considered in this paper do not appear to have a bearing on change in economic performance either. For instance, a dummy that accounts for net total liabilities before privatization usually does not yield a statistically significant link with the change in performance variables considered, and when it does, it is at ten percent and with the wrong sign (operating efficiency). On the other hand, average sales before privatization is statistically significant with change in profitability only, while a dummy that accounts for the presence of unions has no bearing on performance change. However, some country-specific variables do appear to have a bearing on change in firm performance. In particular, a dummy that accounts for whether the country has pursued economic reforms yields a positive sign, which is statistically significant at five percent or better with respect to change in penetration and change in profitability. However, such a variable is only weakly significant with respect to change in operating efficiency in the absence of a regulatory agency dummy.

6 Summary statistics for all the variables used are presented in Appendix 1.
7 Moreover, we do not obtain the expected sign.

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#### **4. Conclusions**

In a context in which state-owned enterprises still represent a sizable fraction of the world’s gross domestic product, investment, and employment (Kikeri, 1999) and in light of the current political sensitivities towards privatization in several regions, we provide evidence on the benefits of CEO replacement before privatization that complements López-de-Silanes (1997) by showing that actual firm restructuring may be the missing link between CEO replacement and privatization prices. From a policy perspective, our research helps provide a better understanding of what works and what does not work in privatization programs, and thus may help improve the design of future programs. In fact, as actual firm reform appears to be the mechanism at play between CEO replacement and privatization prices, governments should weigh the trade-off between political costs and economic benefits of restructuring the firm.

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#### **References**

Barberis, N., M. Boycko, A. Shleifer et al. 1996. “How Does Privatization Work? Evidence from the Russian Shops.” _Journal of Political Economy_ 114: 764-790.

Chong, A., and F. López-de-Silanes. editors. 2002a. “Costs and Benefits of Privatization in Latin America.” Washington, DC, United States: Inter-American Development Bank.

Manuscript.

----. 2002b. “Privatization and Labor Force Downsizing Around the World.” New Haven, United

States: Yale University. Forthcoming as NBER Working Paper.

International Telecommunication Union (ITU). 2002. _Yearbook of Statistics Telecommunication_ _Services 1991-2000_ . Geneva Kikeri, S. 1999. “Privatization and Labor: What Happens when Governments Divest?” World Bank Technical Paper 396. Washington, DC, United States: World Bank.

La Porta, R., and F. López-de-Silanes. 1999. “The Benefits of Privatization: Evidence from Mexico.” _Quarterly Journal of Economics_ 114(4): 1193-1242.

López-de-Silanes, F. 1997. “Determinants of Privatization Prices.” _Quarterly Journal of_ _Economics_ 112(4): 965-1025.

Rosen, S. 1992. “Contracts and the Markets for Executives.” In: L. Werin and H. Wijkander, editors. _Contract Economics_ . Oxford, United Kingdom: Blackwell.

Wallsten, S. 2001. “An Empirical Analysis of Competition, Privatization, and Regulation in Africa and Latin America.” _Journal of Industrial Economics_ 49(1): 1-19.

World Bank. 2001. World Development Indicators. Washington, DC, United States: World Bank. CD-ROM.

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Variable _**Privatization Characteristics**_

**Table 1. Definition of Variables**

Description CEO change Dummy variable equal to 1 if the company changed CEO up to three years prior to privatization, 0 otherwise (Chong and Lopez-de-Silanes, 2002).
Foreign participation Dummy variable equal to 1 if foreign participation was allowed in the privatization process, and 0 otherwise (Chong and Lopez-de-Silanes, 2002).
Share sold Percentage of firm's shares sold in privatization (Chong and Lopez-de-Silanes, 2002).
Independent agency Dummy variable equal to 1 when an independent regulatory agency was established, and 0 otherwise. An independent agency means that the country has a regulatory agency not directly under control of a ministry (Wallsten, 2001) .

_**Firm Characteristics**_ Penetration Percentage change between the two-year average of firm lines per 100 inhabitants before CEO change and the two-year average after CEO change (WorldScope, 2001; International Telecommunications Union, 2002).
Operating eficiency Percentage change between the two-year average of firm lines per employee before CEO change and the two-year average after CEO change (WorldScope, 2001; International Telecommunications Union, 2002).
Profitability Change between the two-year average of return on sales before CEO change and the two-year average after CEO change (WorldScope, 2001; International Telecommunications Union, 2002 ; Bloomberg and Economatica).
Net total liabilities Dummy variable equal to 1 if net total liabilities are greater than zero up to three years prior to privatization, and 0 otherwise (Chong and Lopez-de-Silanes, 2002).
Sales The net present value of the three-year average of firm sales before CEO change. The sales value were denominated in US$ of the initial year (Chong and Lopez-de-Silanes, 2002).
Presence of unions Dummy variable equal to 1 if firm had unions or strikes up to three years prior to privatization, and 0 otherwise (Chong and Lopez-de-Silanes, 2002).

_**Country-Specific Variables**_ Economic growth Average rate of growth of the country three years prior to privatization (World Bank, 2001).
Gross domestic product Gross Domestic Product (US$ PPP) in logs. Average of the three years prior to privatization (World Bank, 2001).
Urban population Average percentage of urban population three years prior to privatization (World Bank, 2001).
Expropriation risk Index that can take values between 0 and 10, with lower scores indicating a lower risk of expropriation (ICRG’s risk ratings).
Economics reforms Dummy variable equal to 1 if telecom privatization took place in an economics reform context (World Bank).
Continental dummies Dummy equal to 1 if to account for the following regions: Latin America, Middle East and Africa, Transition Economies, 0 otherwise.

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**Table 2. CEO Change and Pre-Privatization Performance**

Variables Penetration Operating Efficiency Profitability _**1.- Privatization Characteristics:**_ CEO change 0.3583 *** 0.3574 *** 0.5800 ** 0.5776 ** 0.0722 ** 0.0722 ** (0.095) (0.095) (0.274) (0.266) (0.033) (0.033) Foreign Participation -0.1128 -0.0722 -0.3208 -0.2179 0.0669 - 0.0679 (0.123) (0.123) (0.261) (0.259) (0.039) (0.040) Share Sold -0.0023 -0.0007 -0.0097 -0.0055 -0.0022 - -0.0021 (0.004) (0.004) (0.011) (0.009) (0.001) (0.001) Independent Agency -0.2393 ** -0.6067 ** -0.0063 (0.097) (0.229) (0.027) _**2.- Firm characteristics:**_ Net total liabilities 0.0875 0.0488 0.4488 - 0.3505 0.0367 0.0357 (0.107) (0.104) (0.256) (0.222) (0.033) (0.034) Sales 0.0026 0.0011 0.0064 0.0025 -0.0039 ** -0.0039 ** (0.004) (0.004) (0.015) (0.015) (0.002) (0.002) Presence of unions -0.0011 -0.0972 -0.1631 -0.4068 0.0230 0.0204 (0.251) (0.244) (0.364) (0.372) (0.049) (0.053) _**3.- Country-Specific Variables:**_ Economic Growth 0.0222 0.0220 0.0624 0.0617 *** 0.0049 0.0049 (0.018) (0.016) (0.072) (0.068) (0.005) (0.005) Gross Domestic Product -0.0092 0.0069 -0.0790 -0.0381 -0.0256 - -0.0252 (0.034) (0.031) (0.093) (0.092) (0.012) (0.012) Urban Population -0.0178 *** -0.0175 *** -0.0199 *** -0.0191 *** 0.0013 0.0013 (0.003) (0.003) (0.006) (0.005) (0.001) (0.001) Expropriation Risk 0.0160 0.0265 -0.0040 0.0227 -0.0728 ** -0.0725 ** (0.051) (0.050) (0.123) (0.117) (0.017) (0.017) Economics Reforms 0.2653 ** 0.1919 - 0.4510 - 0.2648 0.1087 *** 0.1068 ** (0.118) (0.112) (0.244) (0.226) (0.040) (0.040) Latin America 0.5677 *** 0.5879 *** 1.4845 ** 1.5358 *** -0.0580 -0.0575 (0.174) (0.154) (0.586) (0.558) (0.054) (0.054) Asia 0.7435 ** 0.7280 - 0.3214 0.2822 -0.1492 *** -0.1496 *** (0.307) (0.315) (0.543) (0.559) (0.052) (0.052) Africa and Middle East 0.2725 0.3020 -0.4543 -0.3795 -0.1276 ** -0.1268 ** (0.253) (0.243) (0.388) (0.393) (0.056) (0.056) Transition Economies 0.3140 *** 0.2869 ** 0.3731 0.3044 -0.1038 ** -0.1045 ** (0.142) (0.138) (0.351) (0.350) (0.044) (0.045) Constant 1.3200 0.9251 3.7332 2.7318 1.2463 *** 1.2359 *** (0.900) (0.930) (2.573) (2.662) (0.371) (0.376) Observations 77 77 77 77 77 77 R-squared 0.73 0.76 0.50 0.54 0.62 0.62 F 12.81 15.54 5.47 6.59 3.85 3.62 Prob > F 0.000 0.000 0.000 0.000 0.000 0.000 Robust standard errors in parentheses

- significant at 10%; ** significant at 5%; *** significant at 1%

13

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Input:
**Appendix 1. Summary Statistics**

Variable Obs Mean Median Std. Dev. Min Max _**Privatization Characteristics**_ CEO change 77 0.468 0.000 0.502 0.000 1.000 Foreign Participation 77 0.870 1.000 0.338 0.000 1.000 Share Sold 77 34.612 30.000 19.676 1.000 95.000 Independent Agency 77 0.351 0.000 0.480 0.000 1.000 _**Firm Characteristics**_ Penetration 77 0.534 0.265 0.617 0.001 2.431 Operating efficiency 77 0.862 0.351 1.231 -0.350 6.418 Profitability 77 0.059 0.040 0.165 -0.476 0.792 Net total liabilities 77 0.468 0.000 0.502 0.000 1.000 Sales 77 3.545 1.430 5.079 0.003 21.991 Presence of unions 77 0.870 1.000 0.338 0.000 1.000 _**Country-Specific Variables**_ Economic growth 77 2.928 3.319 3.726 -11.144 12.822 Gross Domestic Product 77 25.382 25.571 2.176 19.448 28.856 Urban Population 77 66.198 70.500 19.778 12.853 100.000 Expropriation Risk 77 2.221 2.000 1.510 1.000 7.000 Latin America 77 0.247 0.000 0.434 0.000 1.000 Asia 77 0.104 0.000 0.307 0.000 1.000 Africa and Middle East 77 0.117 0.000 0.323 0.000 1.000 Transition Economies 77 0.156 0.000 0.365 0.000 1.000 14

A dataset, survey, database, index, census, registry, or information system with a specific proper name that can be cited, queried, or downloaded as a data source

A data source described by its characteristics or producer rather than a proper name, containing a data noun and at least one identifying descriptor

A general reference to data, information, or statistics that contains a data noun but lacks enough specificity to identify the exact source


Input:
**Appendix 2. Firm and Country Sample**

C om pany C o untry Y ear of privatization A lbanian M ob ile C om m unications A lb ania 2000 B elgacom B elgium 1995 B elize T elecom m unication s L td. B elize 1988 B ezeq Israel 1998 B ritish T elecom U n ited K ingdo m 1984, 1991 B ulgarian T elecom m un ications C o. B u lgaria 2000 C A N T V V enezuela 1991 C T E E l S alvador 1998 C abo V erde T eleco m C ape V erde 1995 C hina T elecom - H on g K ong L td. C h in a 1997 C om pania de T elefon os C hile (C T C ) C h ile 1988 D eutsche T elekom G erm an y 1996, 1999 E N T E L B o livia 1995 E m b ratel S A B razil 1998 E ntel and C P T P eru 1994 E ntel- T eleco m S A A rgentina 1990 E ntel- T elep honica de A rgen tin a S A A rgentina 1990 E sto nia T elecom E ston ia 1993, 1999 F rance T elecom F ran ce 1 997, 19 98 G hana T elecom G h ana 1996 G uyan a T elephone and T elegrap h G u yana 1991 H rvatske T eleko m u nicacije C ro atia 1999 IN D O S A T Indonesia 1994 IN T E L E l S alvador 1998 IN T E L S A P an am a 1997 Jordan T elecom Jordan 2000 K orea T elecom K orea, R ep. 1999 L attelekom L atvia 1994 L ietu vos T elekom as L ithuania 1998 N T T Japan 1987, 1 988, 199 8, 1999 P .T .T elkom Indonesia 1995 P o rtugal T elecom P ortugal 199 5, 1996, 1997 P u erto R ico T eleph one C o . (P R T C ) P uerto R ico 1999 Q -tel Q atar 1998 R oyal K P N N eth erlands 1994, 1995 S K A N T E L S t. K itts and N evis 1992, 1994 S P T T elecom C zech R epublic 1994 S in gapore T elecom m u nications S ingapore 1993, 1996 S o natel S en egal 1997 S o nera F inlan d 1998, 1999 S ri L anka T elecom m unications S ri L anka 1997 S vyazinvest R u ssian F ederation 1997 S w isscom S w itzerland 1998 T ele C entro S ul B razil 1998 T eleD anm ark D enm ark 1998 T elecom E ireanne Ireland 1996 T elecom Italia Italy 1997 T elecom S erbia Y u goslavia, F R 1997 T elecom m unication s of Jam aica (T O J) Jam aica 1990 T elefon ica del P eru P eru 1996 T elekom A ustria A u stria 1998 T elekom unikacja P olska S A P olan d 1998, 2000 T elesp C elular P articipaco es S A B razil 1998 T elfonica S pain 1997 T elgua G u atem ala 1998 T elia S w eden 2000 T elkom S ou th A frica 1997 T elstra A u stralia 1997, 1999 T elus C anada 1990 T rinidad and T obago T elephon e C o. (T & T T ) T rinidad an d T obago 1989 U gand a T elecom m unications L td U ganda 2000 15

A dataset, survey, database, index, census, registry, or information system with a specific proper name that can be cited, queried, or downloaded as a data source

A data source described by its characteristics or producer rather than a proper name, containing a data noun and at least one identifying descriptor

A general reference to data, information, or statistics that contains a data noun but lacks enough specificity to identify the exact source