Cultural and Economic Globalization: Baseball and Foreign Direct Investment

In 2014, 26.3% of Major League Baseball’s active players were from places outside the United States.[i] In the 1970 that number was only 12.3%. Baseball has gone global. So has money. In that same time frame, the total amount of foreign direct investment in the world has by over $1.2 trillion.[ii] In Figures 1-4, we can see that for several countries these increases appear to be correlated. But is one affecting the other? It is hard to separate cultural globalization from economic globalization and even harder to determine which comes first. This analysis uses the exportation of baseball players from other countries to the United States’ Major League baseball as a measure of cultural globalization and investigates its impact on the amount of foreign direct investment coming into a country, a measure of economic globalization. Specifically, the analysis explores the possibility that as a country opens itself up culturally, its increasing openness and new connections to the outside world result in economic globalization.

Figure 1

Figure 2

Figure 3

 Figure 4

The globalization of sport and its impacts on nations has been evaluated extensively in the sports community. Baseball has been argued as a means to further US political interests by serving as a non-threatening, benevolent cultural institution of the United States and softens responses to US involvement in a country.[iii] There is also obvious economic benefits to transnational corporations as foreign born players create foreign born fans looking to check in on native sons in the big leagues and transnational corporations benefit immensely from the opening of new baseball markets.[iv] The explanation for the increase in foreign direct investment has often been attributed to the liberalization of trade and globalization[v] and scholars have attempted to quantify the effect of “informal institutions” on a country’s involvement in and openness to foreign direct investment, finding significant results[vi]. Cultural globalization can be considered as one those informal institutions however, scholarship has yet to explore potential measurements for cultural globalization that can be separated from economic globalization. Sports literature clearly illustrates baseball as a form of cultural globalization and even discusses its role in opening up a country’s inhabitants to outside influence. Using baseball as measurement of cultural globalization then, provides a way independent enough from economic globalization to hold a real analysis on the relationship between economic and cultural globalization.

The analysis includes the impact of other variables that could confound the results if not accounted for: previous FDI, average income, amount of exports, and the amount of natural resources.[vii] In order to ensure there was no possibility of finding results where it might be foreign direct investment impacting baseball players exported to the United States instead of the reverse, a statistical model that matches the number of baseball players in one year to the amount FDI[viii] three years later is used. The other variables in the model have been similarly lagged two years behind FDI for continuity. In short, the model is designed to account for the time it takes for impacts to occur and control for variables that differ between countries but not over time.[ix] For example, the model can control for the long standing embargo the United States has against Cuba and how that might impact both FDI and players exported to the United States.

Table 1. Regression Models for MLB Players on FDI

DV: Foreign Direct Investment	Model 1	Model 2	Model 3
Number of Players in Major League Baseball	0.04*** (8.03)
# of Players in MLB (Lagged 3 years)		0.04*** (7.71)	0.005* (2.14)
Foreign Direct Investment for the Year Before			0.584*** (22.31)
GNI per capita (constant 2005 US$)(Lagged 2 Yrs)			0.000* (2.48)
Total natural resources rents (% of GDP) (Lagged 2 Yrs)			-0.028*** (-3.57)
Logged Exports (Lagged 2 Yrs)			0.429*** (9.55)
R^2 Observations	0.05 1256	0.05 1200	0.79 885

Note: OLS estimates with t-stats in parentheses.* p < 0.05, ** p < 0.01, *** p < 0.001

Sources: World Bank Development Indicators, BaseballReference.com

Table 1 above shows the complete results of the analysis. The first model shows a simple regression without considering potential bias while models 2 and 3 provide a more accurate analysis. Model 3 reflects the complete model and demonstrates that an increase in the number of baseball players does correspond to later increase FDI for a country. The coefficients of the impact for each variable are at statistically significant meaning they we can reject the concept that the correlation is the result of random chance and assert that there is a real correlation between baseballers in MLB and FDI into a country. While the size of the coefficients for the variables appear small, the fact that the dependent variable is logged means that these are percentage changes not changes in raw numbers which makes them more impactful.

This analysis shows that cultural globalization as demonstrated by the exportation of baseball players to MLB does have an impact on later economic globalization as measured by foreign direct investment. While we should better evaluate how good of a measurement of cultural globalization that players in MLB actually is before we can draw further conclusions from this model, the evidence lends itself to the argument that baseball players can affect FDI. We should note the argument that some initial foreign direct investment may have been necessary in order to groom future professional baseball players but there is still a clear uptick in FDI that follows an increase in the exportation of baseball players.

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[i] http://m.mlb.com/news/article/70623418/2014-opening-day-rosters-feature-224-players-born-outside-the-us

[ii] https://www.globalpolicy.org/component/content/article/213/45740.html

[iii] Klein, Alan. 1989. “Baseball as Underdevelopment: The Political Economy of Sport in the Dominican Republic”. Sociology of Sport Journal 6, no. 2: 95-112.

[iv] Marcano, A.J. & Fidler D.P. 2000. “The Globalization of Baseball: Major League Baseball and the mistreatment of Latin American talent”. Indiana Journal of Global Legal Studies 6, no. 2: 511-577.

Gems, Gerald & Pfister, Gertrud. 2014. “Sport & Globalization: power games in a New World order.” Movement and Sport Science 86: 51-62.

[v] Volos, Ch. K, I.M. Kyrianidis, and I.N. Stouboulos. 2015. “The Effect of Foreign Direct Investment in Economic Growth from the Perspective of Nonlinear Dynamics”. Journal of Engineering Science and Technology Review 8, no. 1:1-7.

Landefeld, J. Steven & Whichard, Obie G. 2006. “The importance of, and pitfalls in, measuring globalization”. Statistical Journal of the UN Economic Commission for Europe 23, no. 2/3: 127-142.

[vi] Seyoum, Baley. 2011. “Informal Institutions and Foreign Direct Investment”. Journal of Economic Studies 45, no. 4: 917-40.

[vii] A full table of summary statistics with explanations for the variables in the model is available in the appendix.

[viii] The amount of FDI and exports were logged before inclusion in order to better account for the positive skew of the raw numbers.

[ix] A fixed effects model was employed and a Hausman Test showing the utility of using a fixed effects model over a random effects model is available in the appendix.

Appendix

Summary Statistics Table for Blog Post 2

	Mean	Std. Dev.	Min.	Max.	Description
Net Foreign Direct Investment (Logged)	21.13	2.37	11.00	26.26	The log of the net amount of Foreign Direct Investment received (Source: WBDI)
Players in MLB	7.03	20.70	0.00	160.00	Number of Players in MLB by Country (Source: BaseballReference.com)
Natural Resource Rents	5.03	7.51	0.00	58.18	Total amount received for exportation of Natural Resources (US$) (Source: WBDI)
GNI per capita	15401.80	14478.53	252.86	67582.69	Average Income for a Country’s Population (US$) (Source: WBDI)
Merchandise Exports (Logged)	23.93	2.26	18.45	28.02	The log of the amount of merchandise exported (Source: WBDI)

Hausman Test Results Table

Variable	Fixed Effects Coefficient	Random Effects Coefficient	Difference	Standard Error of the Differences
Players in MLB (3-Yr. Lag)	.0048731	.0006802	.0041929	.0018432
FDI (1-Yr. Lag)	.5836586	.7931641	-.2095055	.0177884
GNI per Capita (2-Yr Lag)	.0000174	2.18e-07	.0000172	6.60e-06
Natural Resource Rents (2-Yr Lag)	-.0278745	-.0031953	-.0246792	.0070134
Exports (Logged, 2-Yr Lag)	.4292305	.1635982	.2656323	.0394832
chi2(5) = (b-B)'[(V_b-V_B)^(-1)](b-B) = 143.55      Prob>chi2 =      0.0000

The Hausman test reveals that error term for the random effects model is actually correlated with the regressors. As a result, the random effects model cannot be considered accurate and a fixed effects model should be employed.