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Economics Letters 105 (2009) 39–41

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Economics Letters

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The effect of the Internet on economic growth: Evidence from cross-country panel data☆

Changkyu Choi, Myung Hoon Yi ⁎ Department of Economics, Myongji University, 50-3 Namgajwadong, Seodaemungu, Seoul 120-728, Republic of Korea

☆ Wewould like to thank Kyeongwon Yoo, Yong-Hwan their comments at the International Finance Study Grou Korea, November 2005. ⁎ Corresponding author. Tel.: +82 2 300 0685; fax: +

E-mail address: [email protected] (M.H. Yi).

0165-1765/$ – see front matter © 2009 Elsevier B.V. Al doi:10.1016/j.econlet.2009.03.028

a b s t r a c t

a r t i c l e i n f o

Article history: Received 12 November 2003 Received in revised form 16 January 2009 Accepted 10 March 2009 Available online 18 May 2009

Keywords: Internet Growth Panel data

JEL classification: C23 L86 O40

Using cross-country panel data, we found evidence that the Internet plays a positive and significant role in economic growth after investment ratio, government consumption ratio, and inflation were used as control variables in the growth equation.

© 2009 Elsevier B.V. All rights reserved.

1. Motivation

The Internet has influenced the economy in every respect. The history of the Internet, however, is not that long. Also, there is little research on the Internet and economy.

The effect of computers, as opposed to the Internet, on an economy has been studied. For example, Krueger (1993) analyzed the effect of computer use onwage structure usingCurrent Population Surveys (CPS) data and found that workers who use computers earn higher wages. Sichel (1999) found that computer hardware contributes to economic growth. Oliner and Sichel (2000) and Oliner et al. (2007) said that productivity growth after 1995 in theUShas beendriven in large part by greater use of information capital goods. Gust and Marquez (2004) found that productivity divergence is driven in part by differences in both the production and adoption of information technologies, and that the adoption of information technologies has been impeded by regulatory labor market practices. According to Freund and Weinhold (2004) and Choi (2003), the Internet has had a positive effect on bilateral trade and foreign direct investment, respectively. Yi and Choi (2005) found that the Internet lowers the inflation rate by cross-country panel data analysis.

With broad use of the Internet starting in the 1990s, we used cross- country panel data to gather enough observations to analyze the

Noh and other participants for p seminar held at the Bank of

82 2 300 0654.

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Internet-growth nexus. In Section 2, we derived a simple growth equation incorporating the Internet variable. In Section 3, we perform several estimations for the growth equation. Section 4 concludes the paper.

2. Model

Romer's (1986, 1990) endogenous growth model explains that balanced growth is positively influenced by knowledge spillover. We hypothesize that the Internet plays a great role in spreading knowledge in an economy. Therefore, economic growth is positively related with the use of the Internet. FromBarro's (1997) growth equation,we choose the ratio of investment to GDP, the ratio of government consumption to GDP, and inflation as explanatory variables along with our Internet variable. Therefore the real per-capita GDP growth rate is determined by the Internet, investment, government consumption, and inflation. We set the following growth equation for estimation,

Growthit = β0 + β1Internetit + β2Investmentit + β3Governmentit + β4Inflationit + uit; ð1Þ

where uit=ηi+vt+εit, ηi is an individual (country) effect, and νt is a time effect, and εit is independently and identically distributed among countries and years. Growthit is the real per-capita GDP growth rate of country i at year t; Internet is the ratio of the Internet users to total population; Investment is the ratio of gross domestic investment to GDP; Government is the ratio of government expenditure to GDP. The coefficient of Internet is expected to be positive as it contributes to the

Table 1 The Internet and economic growth.

(a)a (b) (c) (d) (e) (f)a,b

Pooled OLS Individual random Individual fixed Time fixed Individual random and time fixed Panel GMM

Constant −1.173⁎ (0.701) −1.447⁎ (0.742) −1.186 (0.801) 0.389 (1.070) Internet 5.710⁎⁎⁎ (1.566) 5.641⁎⁎⁎ (2.018) 4.931⁎⁎ (2.194) 5.886⁎⁎⁎ (2.034) 5.678⁎⁎ (2.324) 5.517⁎⁎⁎ (1.724) Investment 0.167⁎⁎⁎ (0.023) 0.195⁎⁎⁎ (0.024) 0.281⁎⁎⁎ (0.038) 0.168⁎⁎⁎ (0.019) 0.197⁎⁎⁎ (0.024) 0.085⁎⁎ (0.041) Government −0.039 (0.032) −0.061⁎ (0.031) −0.198⁎⁎⁎ (0.071) −0.033 (0.022) −0.054⁎ (−0.032) −0.024 (−0.034) Inflation −0.003⁎ (0.001) −0.003⁎⁎⁎ (0.0004) −0.003⁎⁎⁎ (0.0005) −0.003⁎⁎⁎ (0.0004) −0.003⁎⁎⁎ (0.0004) 0.001 (0.002) R2 0.27 0.43 0.46 0.29 0.45 J-statistic [p-value] 10.320 [0.112] Sample size 1004 1004 1004 1004 1004 565

⁎⁎⁎, ⁎⁎, and, ⁎ indicate significance at the 1%, 5%, and, 10% levels, respectively. Standard errors are in parentheses. a Newey and West's (1987) heteroscedasticity and autocorrelation consistent covariance matrix assuming a lag length of one is used for standard errors. b Instrumental variables include constant, (Growth)t−2, t−3, (Internet Users/Pop)t−2, t−3, (Gross Investment/GDP)t−2, t−3, (Government Expenditure/GDP)t−2, t−3, (Inflation)t−2, t−3.

40 C. Choi, M.H. Yi / Economics Letters 105 (2009) 39–41

knowledge spillover. The coefficient of Investment is expected to have a positive sign (Levine and Renelt, 1992; Mankiw et al., 1992; DeLong and Summers, 1991). The coefficient of Government is expected to be negative as the government distorts the private decisions (Barro, 1997). As high inflation is known to be associated with low economic growth in general, the coefficient of Inflation is expected to be negative (Barro, 1995; Fernández Valdovinos, 2003).

3. Data and empirical results

Data for 207 countries from 1991 to 2000 were taken from the World Development Indicators 2002 CD-ROM of World Bank (2002). Internet users, the number of people with access to the worldwide network, are divided by total population to get the internet users ratio. Annual percentage growth rate of GDP per capita (gross domestic product divided by midyear population) is based on a constant local currency. Gross domestic investment consists of outlays on additions to the fixed assets of the economy plus net changes in the level of inventories. General government final consumption expenditures include all government expenditures for purchases of goods and services. Inflation is measured by the consumer price.

Table 1 lists the regression results.We estimated thegrowth equation (Eq. (1)) by various estimation methods: (a) pooled ordinary least squares (OLS), (b) individual random effects, (c) individual fixed effects, (d) time fixed effects, (e) individual random effects and time fixed effects, and (e) generalized method of moments (GMM) estimation.

According to the benchmark pooled OLS regression (column (a) in Table 1), the estimated coefficient of Internet is 5.710 and significant at the 1% level as expected. This means that when the Internet–user ratio increases by 1% point, the growth rate increased by 0.057% point. The estimated coefficient of Investment is 0.167 and significant at the 1% level. This means that when the investment ratio increases, growth rate increases, too. The estimated coefficient of government consumption is insignificant. The estimated coefficient of Inflation is −0.003 and significant at the 10% level.When the inflation rate increases by1%point, growth rate decreased by 0.003% point.

As we used panel data in our regressions, we re-estimated the growth equation (Eq. (1)) by panel data regression methods such as individual random effects (column (b) in Table 1), individual fixed effects (c), timefixed effects (d), and individual randomeffects and time fixed effects (e). The estimated coefficients of Internet range from 4.931 to 5.886 and are significant at the 1% level in (b) and (d) and at the 5% level in (c) and (e). This means that when the Internet–user ratio increases by 1%point, the growth rate turned out to increase by between 0.049 and 0.059% point. The estimated coefficients of Investment are very similar to pooled OLS estimation in (a). The estimated coefficients of government consumption are negative and significant at the 10% level in equations (b), (c), and (e). The estimated coefficients of Inflation are all negative and significant at the 1% level.

Because explanatory variables such as the Internet, investment ratio, and government consumption ratio, can be influenced by economic growth, we performed GMM estimation to take into account any endogeneity of the explanatory variables (column (f) in Table 1). The coefficient of Internet is 5.517 and significant at the 1% level. The coefficient of Investment is 0.085 and significant at the 5% level. The coefficient of government consumption and inflation proved to be insignificant. Hansen's (1982) J-statistic is 10.320with a p-value of 0.112, suggesting that themodel iswell specified (Hansen andSingleton,1982).

To sum up, the effect of the Internet on economic growth is positive and significant across all the regressions. Furthermore the regression coefficients of investment, government consumption, and inflation are mostly consistentwith the standard results in the literature. Investment has a positive effect on economic growth, and government consumption and inflation have a negative impact on economic growth. This means that the result is quite robust against different estimation methods.

4. Conclusion

The Internet is assumed to contribute to the spillover effect of knowledge across countries. Therefore, the increase in the use of the Internet in a country is hypothesized to have a positive impact on economic growth. Using panel data with 207 countries from 1991 to 2000, we found evidence that the Internet plays a positive and significant role in economic growth after investment ratio, government consumption ratio, and inflation were used as control variables in the growth equation.

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