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Do late movers have advantages? an empirical investigation in the global wine export industry.

INTRODUCTION

The global wine industry has for decades faced an intensified competition, as dominant early movers from the Old World (1) are losing market share to the New World (2) late movers. At the same time, the New World players struggle amongst themselves to share the pie, increasing competition that has spurred the export of global wine volume. Now, a shift to worldwide higher quality wine consumption is challenging late movers' low cost strategy of selling cheap wine. Therefore, how late movers gain a competitive advantage is our research topic. Specifically, we want to know whether late movers gain advantages by pursuing a low cost strategy or by employing a differentiation strategy. The former involves producing cheap and low quality wine to draw price-conscious wine drinkers, while the latter approach focuses on upgrading the quality of low-priced wine in order to attract more upscale wine drinkers.

Over the last 25 years, the global wine industry has undergone several structural changes. First, from 1987 to 1997, global wine production fell to 0.8 percent annually, all the while global wine trade activities rose by 4.1 per cent in volume and 6.5 percent in value annually (Anderson, 2001). This indicates that the speed of wine production slowed down, while the velocity of wine trade activities increased. Second, researchers have observed a change in wine consumption patterns, whereby consumption of better quality wine has grown steadily, while poor quality wine consumption has declined (Anderson, 2003). Some investigators observe that consumers have been drinking less but better wine over the last decades (Heien & Martin, 2003). Third, both late movers from the New World and early movers from the Old World increased their wine trade, further contributing to an oversupply of wine. This puts additional pressure on wine price and intensifies competition. Therefore, factors that affect wine exports become an interesting research area to explore (Witter, Berger, & Anderson, 2003).

Trying to identify key success factors for New World late movers yields various responses. In the New Zealand wine industry, for example, Mikic (1998) attributes this country's success to trade liberalization and a change from import substitution to export orientation. Barker et al., (2001) emphasizes that factors such as local conditions, historical background and innovation, have a stronger influence on wine exports. Still others propose that the success of wine exports lies in the governance of the evolution of global commodity chains connecting growers of grapes, producers of wine, marketers and distributors to the final consumers (Gwynne, 2006).

Using data from 16 wine export countries, we examined factors that influence wine export volume. They cover issues of wine quality, R&D investment, comparative advantages in wine production and market power as influencing wine export price. The study makes two contributions to the understanding of the wine export industry. First, instead of assembling different qualitative assessments of wine quality, this study applies a simple classification of bottled vs. bulk. The bulk wine sector reflects low price and low quality, while the bottled wine sector represents high price and high quality. Late movers specifically sought to upgrade low quality and low priced bulk wine into high quality and high priced bottled wine through a shift in strategy from cost leadership to differentiation in order to improve wine quality. Second, in comparison with late movers, early movers have seemingly two advantages. They enjoy comparative advantages in producing bottled wine and also a great degree of market power in charging a higher price for bottled wine in the export market. However, these advantages fail to strengthen the export of bottled wine by early movers, suggesting late movers can indeed break into the bottled wine export market dominated by early movers. As a result, competition in the bottled wine export market intensifies as gradually more and more late movers are able to enter the market and share the pie. In other words, although it is commonly accepted that late movers gain market share by exporting low price and poor quality wine, they are also capable of exporting better quality wine to compete with early movers, a result that is not always expected.

The rest of the paper is organized in the following way: section two presents the literature review; data and methods appear in section three. Panel data analysis and results are reported in section four. Section five concludes the paper.

ADVANTAGES OF LATE MOVERS

The consumption of wine started its rapid growth when the healthy benefits of drinking wine was scientifically studied and publically reported in the early 1990s, driving up wine expenditures by health conscious consumers (Bisson, Watrhouse, Ebeler, Walker, & Lapsley, 2002). During the last two decades, structural changes in wine consumption markets have intensified the competition. On the one hand, late movers such as Australia, Chile and the U.S. began competing with early movers to export to the traditional wine consumption markets that were dominated by Old World producers such as France, Italy and Spain. In addition, consumption of wine per capita in France, Italy and Spain has declined by 40-50% over the last 30 years, leading to the oversupply of Old World wine (Bisson et al., 2002) and intensifying competition in the world wine market. On the other hand, new wine consumption markets have emerged, such as the U.S., Britain and Scandinavian countries, forming a new global market for both New World and Old World wines (Campbell & Guibert, 2006). Also, at the same time, consumers from newly emerged wine consumption markets have learned to appreciate quality wine over low priced wine, creating an opportunity that late movers have responded to, known as early movers' advantage (Campbell & Guibert, 2006).

Early movers specifically enjoyed the timing advantage (Lieberman & Montgomery, 1988, 1998). According to a resource-based view, early movers were better able to accumulate resources and capabilities over time than late movers and preempted resources of various types, such as geographic locations and customer perception (Lieberman & Montgomery, 1998). As a result, early movers gained a competitive edge. For example, in the wine market, early movers shaped wine quality appreciation standards, and consumers with the accumulated experience of early movers' quality wine may perceive an increased switching cost if they try late movers' products.

Yet late movers are not entirely left out and could respond to early movers' entry advantages (Aaker & Day, 1986; Henderson & Clark, 1990; Henderson, 1993). The choice of business-level strategy, for example, could help late movers to enter and grow in an existing market such as the wine export industry. This was accomplished through two distinctive business level strategies: one is cost leadership strategy, the other differentiation strategy (Porter, 1985). According to Porter, firms applying cost leadership strategy provide good enough products or services with lowest cost relative to that of competitors, and they gain market share by catering to consumers who are price sensitive. Contrary to cost leadership, firms can also use differentiation strategy to fight off competition (Porter, 1985). That is, firms provide goods or services with unique qualities relative to competitors at a premium with acceptable costs. They then gain market share by aiming at consumers who care more about quality and are price insensitive. A focus on quality and innovation is the core for implementing differentiation strategy.

Late movers from the New World can offset the timing disadvantage by practicing cost leadership strategy. By focusing on offering lower priced and lower quality wine than early movers, they are able to attract price conscious customers. In addition, the competitive labor costs from emerging countries that are also populated with late movers could further enhance late movers' capability to produce cheaper wine. The quality issue is less stressed by cost leadership strategy, and price conscious consumers perhaps perceive the likelihood of obtaining good quality wine from new entrants to be low as well. After all, it is early movers who have greatly shaped the industrial standard of wine quality.

Cost leadership strategy works as long as the market for consuming low price and low quality wine exists. Nevertheless, the development of wine consumption behavior over the last decades challenges cost leadership strategy. As outlined earlier, consumers are getting more demanding, they are turning away from the low quality wine associated with cheap price, and are looking for better quality wine with a still reasonable price (Heien & Martin, 2003).

How late movers change the perception of poor quality wine associated with cost leadership strategy, therefore, becomes critical for their survival. We propose that late movers can face the challenge by shifting strategy from cost leadership to differentiation with a focus on improving quality and enhancing innovation. Doing so allows them to retain customer base due to the demand for better quality wine, on the one hand, and still enjoy a relatively competitive pricing structure on the other.

Gaining Advantages from Quality and Innovation

There are various ways to examine the effect of wine quality. Several studies have pointed out that wine quality is associated with wine export volume (Bernetti, Casini, & Marinelli, 2006; Heien & Martin, 2003; Schamel & Anderson, 2003). Others have applied an economic modeling method to understand the effect of wine quality on wine production. Schamel and Anderson (2003), for example, used a Hedonic price model to study how quality of wine affects the premium wine market. Other studies engage a more narrative approach. Bernetti et al. (2006) analyzed the quality issue through emerging trends in wine production, consumption and distribution to predict future production scenarios. They concluded that a strategy with a focus on quality was the key to compete in the wine export market. Shapiro (1983), in an early study, stated that quality could not be known until the wine was consumed, and, thereby, he suggested linking the quality pre-consumption to producer's reputation, which reflected a public record reviewing information consumers could obtain in a competitive market. As a result, reputation allowed wine producers to sell their high-quality wine at a premium. Although quality issue is critical to wine export, the approach to quality is nevertheless diversified. We chose a more generally applied classification of wine quality: bottled wine vs. bulk wine. We selected this classification because bottled wine indicates a high quality wine sector, where wine is produced in containers of two liters or less, while bulk wine represents a low quality wine sector, where wine treatment is not specified (Rothfield & Witter, 2008).

As we mentioned earlier, consumers' wine drinking behavior has shifted over the decades; they are turning towards quality and away from quantity drinking. This phenomenon indicates that wine exporters across countries are likely to shift their production strategy to satisfy the growing segment of quality conscious consumers. This shift is more critical for late movers from the New World, as they generally entered the wine export market by leveraging their price advantages of low quality wine as exemplified by bulk wine production and export (Schamel & Anderson, 2003). Late movers from the New World can respond to the change by replacing cost leadership strategy with differentiation strategy to accommodate this particular trend in consumption behavior. Consequently, they shift their focus from bulk wine production to bottled wine production. Statistics of wine exports from New World countries, such as Argentina, have shown such a market shift in the last decade (Rothfield & Witter, 2008).

A change of cost leadership strategy towards differentiation strategy involves investment in innovation, which is the key to improving wine quality. A revolutionary change to upgrade Chilean wine quality in the 1980s is a good example. This period could be characterized by successfully implementing two innovative processes in wine making: replacing wooden vats with stainless steel vats to ferment the grape and introducing the use of small (220-liter) oak barrels in place of the traditional 4,000-liter "fudres" to store the wine (Agosin & Bravo-Ortega, 2009). It was found that stainless vats could improve the sanitary environment for wine-making, facilitate removing the impact of wine residues on wine taste and smell, and allow better control of the process of fermentation that is a fundamental to making good quality wine (Agosin & Bravo-Ortega, 2009). Meanwhile, innovation also took place in modernizing the old outdated production line and standardizing bottling and corking procedures in the 1980s. All these innovation efforts successfully upgraded Chilean wine quality to match wine appreciation standards at the international level. Innovation is nevertheless costly. For instance, when the first Chilean-owned vineyard, Vina Canepa, started to use stainless steel vats, it financed the huge investment of steel vats of 50,000, 80,000, 100,000 and 200,000 liters with foreign credit, and, in addition, it also paid extra expenditures to train Chilean workers to assemble the vats.

Other initiations have also taken place to enhance innovation efforts in countries from the New World. For example, late movers have encouraged skills and technology transfer from Old World countries to their focal countries; they have fostered cooperation between vineyards and local universities to brew new technologies; they have invested in research and development (R&D) to advance applicable innovations (Agosin & Bravo-Ortega, 2009; Visser & Langen, 2006); and they have benefitted from business networks among clustered firms that have brought higher innovative capacity to improve wine quality (Giuliani, 2007).

Among innovation efforts, R&D is vital to gaining a competitive advantage for late movers. First, a focus on R&D investment, in the long run, can enhance late movers' competitiveness in exploiting and defending market share (Hitt, Ireland, & Hoskisson, 2010). Simply adopting a foreign country's technology can prevent late movers from developing their own technologies that may be more adaptable to their special needs and thus hinder the development of unique competitiveness of late movers. Second, R&D investment at various levels, such as business, community or country level, can trigger a fruitful future cooperation between vineyards and research institutions, with a result that further enhances the quality of wine production. For example, the INNOVA program in Chile that was fostered by R&D investment in the 2000s, with the purpose of encouraging cooperation between vineyards and local universities, has strengthened Chilean vineyards' capability to produce even better quality wine for international export markets (Agosin & Bravo-Ortega, 2009). Third, new technologies can arise from enhanced R&D investment and by joining clustered businesses the benefits of technologies are further spread and absorbed by more wineries and vineyards. Consequently, competitiveness in the wine industry is strengthened at a country level, according to the analysis of nations' competitive advantages (Porter, 1990).

To sum up, R&D is critical for quality improvement. It plays an important role in a successful transfer from cost leadership strategy to differentiation strategy and from the bulk wine market to the bottled wine market. Given a high quality standard demanded by the bottled wine market (as opposed to bulk wine), R&D investment is pertinent to bottled wine exports, regardless of the entry timing of competitors. Not surprisingly, we may not observe this relationship in the bulk wine market. Consequently, this gives us:

Hypothesis 1: R&D investment in wine industry can enhance the export volume of bottled wine for wine producing countries.

Hypothesis 2: R&D investment in wine industry has little impact on the export volume of bulk wine for wine producing countries.

Late Movers' Disadvantages

As discussed earlier, late movers can suffer disadvantages because of their delayed entry, which makes it difficult for them to accumulate and develop capabilities to compete against early movers (Lieberman & Montgomery, 1988, 1998). Wine is a special commodity. Compared with other agricultural commodities such as corn or soybeans, wine is marketed by geographical locations within countries where grapes are produced (known as appellation). This leads to a unique feature that reflects on the quality consumers expect to find (e.g. Bordeaux, Napa, Rapel, Tuscany, Rioja). It thus takes time for a country to build a desirable image of its unique wine culture and industry that is internationally accepted and appreciated, as exemplified by wine from France and Italy.

There are two disadvantages associated with late movers in the wine export market: competitive advantages and market power.

Comparative Advantage: The comparative advantage of wine is an index that captures the contribution of wine exports to a country relative to a global average (Rothfield & Witter, 2008). A higher value reflects a higher signficance of wine exports to a country's trade than it is to global trade in general (Rothfield & Witter, 2008). This advantage reveals the depth of history and culture of wine making in a country, as well as resources and capabilities accumulated over time in wine making. A high comparative advantage of wine index thus indicates a high status of the wine industry relative to other industries in a given country, and, rationally, more resources would be directed to build economies of scale. Therefore, early movers with a stronghold in the wine industry, such as France and Italy, experience a positive effect from comparative advantage of wine index, which is deficient for late movers.

Comparative advantage of wine index is perhaps more important for the quality wine market (bottled wine), as the culture of producing and consuming good quality wine may take longer to form (Anderson, 2003; Heien & Martin, 2003). In the bulk wine market, the comparative advantage of the wine index may have little impact on poor quality wine exports. To sum up, we have the following hypotheses:

Hypothesis 3: The comparative advantage of wine index for a country enhances the country's export volume of bottled wine.

Hypothesis 4: The comparative advantage of wine index for a country bears little impact on the country's export volume of bulk wine.

Market Power: Market power exists when a competitor is able to sell a product above the existing average level (Hitt et al., 2010). In the wine industry, market power can be used to describe a country's influence on a general wine price in the export market. Early entry can help to build market power, as it can facilitate the development of wine production through resource accumulation over time. A high market power of wine index thus indicates a high level of influence on the wine price. Intuitively, early movers in the wine export market perhaps enjoy a higher level of market power than late movers.

Market power is particularly important for quality wine export, i.e. bottled wine export. This is because competition in the quality wine market builds up due to the emerging consumption pattern of quality drinking over the recent years (Heien & Martin, 2003). The relationship between quality wine and price is also found in economic modeling. For example, one study shows that quality monotonically increases the price of wine, market entry and export values (Crozet, Head, & Mayer, 2010), and another shows that a global trend of growing consumption for premium wine offsets the fall in total wine production quantity (Witter et al., 2003). Therefore, market power of a country can be more vital for quality wine export, and this leads to:

Hypothesis 5: A country's market power in bottled wine export is positively associated with the volume of bottled wine export.

METHODOLOGY

Data

We performed a panel data analysis at the country level. Panel data is a set of longitudinal data covering different sections over a period of time. Therefore, panel data is capable of providing multiple observations for individual variables across sections and over time, such that a strong generalization can be drawn (Hsiao, 2003). The availability of panel data in the wine export industry makes this method feasible. The raw data comes from two sources: a public secondary database from World Bank statistics and a private secondary database known as the global wine statistical compendium, 1961-2006 (Rothfield & Witter, 2008). These two databases provide us with wine export information and country-specific macro economic background for 47 countries and regions, ranging from the year 1996 to 2006. We selected to analyze 16 countries (see Table 1). Here, the percentage of wine export over the total wine export, calculated as total wine export from 1996 to 2006 for a country / total wine export from 1996 to 2006 for all 47 countries and regions, is greater than one percent. The wine export percentage information is presented in Table 1.

Table 1: Total Wine Export Between 1996 And 2006

Source: Rothfield, J., & Witter, G. 2008. The global wine statistical compendium, 1961 2006.

Econometric Model

In order to test the performance of wine exports in (wine) producing countries, we used a panel for the sixteen largest export countries for the period 1996-2006 (see Table 1). The dependent variable was wine export volume. We selected a series of explanatory variables according to the hypotheses illustrated earlier and evaluated their effects on the wine export volume through the following econometric equation:

[y.sub.it] = [[alpha].sub.i] + [gamma][y.sub.i,t-1] + [x.sub.it][beta] + [[epsilon].sub.it] (1)

Here, y is the log of total volume exported by country i in year t; X is a row vector of explanatory variables, some of which are endogenous to the wine market and others are exogenous (see Table 2), [[alpha].sub.i] is the individual fixed effect for country i, and [[epsilon].sub.it] is the error term.

We considered that the variables directly related to the determination of market results were endogenous to the model, and this was because they were determined by the volume that producers decided to export in a given year. The exogenous variables corresponded to either measures of characteristics or situations of the economy, or the level of research and development investment in the country.

Among the explanatory variables, we used three measures to capture R&D impact on wine export volume in the wine industry of a given country. Specifically, they were 1) number of researchers per million people, 2) percentage of research and development (R&D) per GDP and 3) technicians in R&D per million people. The comparative advantage of wine is an index that captures the contribution of the wine export to a country relative to a global average (Rothfield & Witter, 2008). The comparative advantage index was collected from the Global Wine Statistical Compendium (Rothfield & Witter, 2008). Market power measures a country's capability to sell wine above existing average price in the wine export market. We operationalized this concept by using the equation, (a country's wine export price--average of wine export price for 16 countries) / average of wine export price for 16 countries.

The remaining variables were control variables. First, we controlled for GDP per capita and population. These two variables reflected the size of the domestic demand for wine, given that a stronger demand in this sector could result in relatively lower production for wine export (Witter et al., 2003). We also controlled for the real exchange rate, which determines the advantage of exporting due to differences in exchange rate with foreign currencies. A higher exchange rate should imply better terms of exchange for exports and, consequently, higher incentives to export wine. Last, we controlled for total value of bottled and bulk wine, as studies have shown that value of wine can have a positive effect on the wine export market (Schamel & Anderson, 2003; Visser & Langen, 2006).

The econometric model (equation 1) is a dynamic panel data model that includes the lagged value of the dependent variable as an explanatory variable (yit-1). However, there are two potential modeling problems with this setup that we should mention: problems caused by the presence of random effects that produce correlation between the error term and the lagged dependent variable (Arellano & Bond, 1991) and those caused by fixed effects estimators that will produce inconsistent estimators. In order to solve these problems of panel data modeling, Arellano and Bond (1991) proposed a methodology of estimation based on the generalized method of moments (GMM) estimation to solve the heterogeneity issue by differentiating equation 1 to obtain equation (2):

[DELTA][y.sub.it] = [gamma][DELTA][y.sub.i,t-1] + [DELTA][X.sub.it][beta] + [[epsilon].sub.it] (2)

However, even though the fixed effects were eliminated from equation (2) the correlation between the lagged dependent variable and the error term was still present. As a result, instrumental variables of the form ([y.sub.it-2] - [y.sub.it-3] or the lagged levels [y.sub.it-2], [y.sub.it-3], could be used to eliminate this problem. In our case, we also assumed that some of the variables in the right hand side of equation (2) were endogenous and needed to be instrumental as well.

ANALYSIS AND RESULTS

In the analysis, we distinguished between the bottled wine and bulk wine market. The bottled wine market requires higher quality, marketing and research and is more suitable for implementing a differentiation strategy. The bulk wine market, on the other hand, is equated with table wines and thus lower quality wines. We applied the same econometric model with a different dependent variable for these two markets. That is, we used the volume of bottled wine export for one model and the volume of bulk wine export for the other. The results for the two markets are presented in Table 3 and 4.

Hypothesis 1 stated that R&D investment will increase the volume of bottled wine export; whereas it will have little influence on the volume of bulk wine export in hypothesis 2. Three different measures were used to analyze R&D impact. The results in Table 3 show that all measurements have provided positive impacts on the volume of bottled wine exports. To assess the overall model, the Sargan test was performed to assess the validity of the over identifying restrictions, and we failed to reject the null hypothesis that the over identifying restrictions are valid in all three models. We also reported the Arellano-Bond result that tests the validity of the GMM estimation, which confirms the presence of no second order autocorrelation. Hypothesis 1 is thus supported. In Table 4, only one of the three measurements shows a positive impact on the volume of bulk wine export, suggesting a weak relationship between the R&D investment and bulk wine export volume and, thus, hypothesis 2 is moderately supported.

In testing comparative advantage on wine export, hypothesis 3 asserted that the comparative advantage will increase the volume of bottled wine export, whereas in hypothesis 4 it will have little impact on the volume of bulk wine export. The results of three models in Table 3, however, all indicate a significant negative impact on the volume of bottled wine export (-0.250***, .209*** and -.378***). Hypothesis 3 is thus rejected. In testing hypothesis 4, the results of the first two models in Table 4 show no significant relationship between the volume of bulk wine export and comparative advantage except a significant negative effect found in the third model (.348*). Overall, hypothesis 4 is supported.

Hypothesis 5 expected that market power would positively influence the volume of bottled wine export, while hypothesis 6 stated that it would bear little influence on the volume of bulk wine export. Similar to the analysis results of comparative advantage in wine export, we found significant negative impacts of market power on the volume of bottled wine export from all three models in Table 3 (-.392***, -.367***, -527***). Hypothesis 5 is thus rejected. In Table 4, there is no significant relationship found between market power and the volume of bulk wine export. Hypothesis 6 is hence supported.

For control explanatory variables, we found, as expected, that higher value for wine exports had a positive effect on the volume of both the bottled and bulk wine export market. Also, as expected, GDP per capita had negative and significant coefficients for both markets, indicating that the higher the purchasing power in the country the lower the level of exports, although the effect was stronger for the bottled wine than the bulk wine market. As for the real exchange rate effect, however, we found a negative and significant effect throughout the three specifications in both Table 3 and 4. This negative effect could indicate that an appreciation of the local currency could increase imports of wines, while leaving a higher volume for exports. Alternately, it may suggest that a volatile exchange rate, as represented by a high exchange rate value, would negatively influence the export volume of wine.

CONCLUSION

In this paper, we aimed to study how late movers in the wine export market gain advantages over dominant early movers from Old World countries such as Spain, France and Italy. We argue that early movers could implement cost leadership strategy to enter the existing wine export market and replace this strategy with differentiation strategy to respond to the emerging consumption pattern of quality drinking. Overall, we found support for the differentiation strategy undertaken by late movers with a focus on innovation to improve wine quality. Our three different specifications, using different measures for R&D investment, show that there is a strong positive effect between the volume of bottled wine export--but not the volume of bulk wine export - and the level of investment in R&D in a given country. This result indicates that the development of quality wine is the key for the bottled wine market.

Hypotheses concerning comparative advantage and market power are rejected, indicating that the benefits of a high comparative advantage and a high level of market power of early movers do not necessarily improve their wine exports. In other words, late movers, who generally lack comparative advantage and market power, are not necessarily hindered in their entrance to the bottled wine market. The recent evolution of the wine market, exemplified by the decline of traditional early movers from export countries, such as France, and the rise of late movers from countries, such as Chile, support our findings that the wine market is very competitive and open to opportunities for new investments (Rothfield & Witter, 2008). This is good news for other potential newcomers from countries such as Romania, Hungary, Moldova and China. These producers could not only enter, but also thrive in the bottled wine market.

There are some weaknesses in this study. First, our data collection is aggregated at the country level, which hinders our direct analysis of individual firms' behavior in the wine market. We could infer from the current analysis at the country level that this is because a country in the wine industry could be viewed as a sum of either early or late movers. Nevertheless, a direct analysis at the firm level will greatly improve our understanding. Second, there may be other influential factors that could affect the volume of wine exports that are not included in our analysis. For example, political stability, particularly in developing countries, may affect a country's exports in general, including wine. Third, the innovation in this study is measured by R&D investment in three general areas. More direct innovation measurements related to the wine industry could generate interesting results in future studies.

Besides the above shortcomings, this study has some interesting results to offer. It highlights the importance of dissecting the total wine export market according to quality standard, as exemplified by bottled versus bulk wine. The paper also concludes that the bottled wine export market is highly competitive, which will continuously attract more newcomers, as dominant early movers are less likely to benefit from their historically accumulated comparative advantages and market power.

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(1) Old World in wine industry refers to traditional European countries with long wine production and consumption history, such as France, Italy and Spain.

(2) New World refers to important wine producing countries from North America, such as the US, and southern hemisphere countries such as Chile, Argentina, South Africa, Australia and New Zealand.

Dr. Pingying Zhang. (Pingying.zhang@unf.edu). Assistant professor in management at Coggin College of Business, University of North Florida, Jacksonville, FL. Her research interests include strategic entrepreneurship, corporate governance and competitive advantages.

Dr. Andres Gallo. (Andres.Gallo@unf.edu). Professor in economics at Coggin College of Business, University of North Florida, Jacksonville, FL. His research interests include institutions and economic development, property rights, political economy, technology and international economics.

Dr. Chris W. Baynard (cbaynard@unf.edu). Assistant professor in economics and geography at Coggin College of Business, University of North Florida, Jacksonville, FL. His research interests include land-use and land-cover change, landscape infrastructure footprint, energy and environment, environmental management and energy policy.
Table 1: Total Wine Export Between 1996 And 2006

                      1996       1997       1998       1999

1     France          6,003.70   5,509.80   5,427.10   6,293.50
2     Italy           5,877.20   5,056.30   5,714.00   5,807.30
3     Spain           3,040.10   3,321.70   3,022.40   3,266.40
4     United States   1,887.70   2,617.60   2,050.00   2,075.00
5     Argentina       1,268.10   1,350.00   1,267.30   1,588.80
6     Australia       673.4      617.4      741.5      851.1
7     Germany         864.2      849.5      1,083.40   1,228.60
8     South Africa    899.3      880.9      815.6      914.1
9     Portugal        948        591.4      358        760.2
10    Chile           382.4      454.9      547.5      480.6
11    Romania         766.3      668.8      507.1      566.1
12    China           437.3      401.3      438.7      489.3
13    Hungary         418.8      447.2      434        333.9
14    Greece          408.5      406.6      453.6      433.3
15    Moldova         409.5      319.2      191.6      216.4
16    Brazil          232        274.3      218.2      319

                      2000       2001       2002       2003

1     France          5,754.10   5,338.80   5,196.60   4,749.10
2     Italy           5,408.80   5,229.30   4,620.00   4,665.00
3     Spain           4,179.00   3,093.70   3,641.90   4,036.90
4     United States   2,660.00   2,300.00   2,540.00   2,350.00
5     Argentina       1,253.70   1,583.50   1,269.50   1,322.50
6     Australia       806.3      1,076.50   1,220.40   1,086.00
7     Germany         1,008.10   898        998.4      819.1
8     South Africa    837.2      746.5      834.2      956
9     Portugal        784.4      671        778.9      714.9
10    Chile           667.4      565.2      574        687
11    Romania         545.3      546.3      546.1      545.7
12    China           534        558.9      561.2      599.7
13    Hungary         429.9      551.4      333.3      388.7
14    Greece          368        355.8      347.7      308.5
15    Moldova         269.9      342.5      371.1      443.8
16    Brazil          300        296.8      312.2      262

                                                       Average
                      2004       2005       2006       Exports

1     France          5,884.50   5,331.40   5,340.00   5,529.87
2     Italy           5,500.00   5,056.20   4,711.70   5,240.53
3     Spain           4,190.60   3,977.30   4,010.00   3,616.36
4     United States   2,241.60   2,546.40   2,338.00   2,327.85
5     Argentina       1,546.40   1,522.20   1,539.60   1,410.15
6     Australia       1,471.20   1,433.80   1,429.80   1,037.04
7     Germany         1,010.70   915        900        961.36
8     South Africa    1,015.70   905.2      1,013.00   892.52
9     Portugal        676.6      705.1      715        700.32
10    Chile           654.5      804.6      845        605.74
11    Romania         616.6      472.9      589.4      579.15
12    China           656.3      733.6      689.6      554.54
13    Hungary         527        442.8      454.4      432.85
14    Greece          381.5      429.5      399.7      390.25
15    Moldova         348.8      350.9      359.7      329.40
16    Brazil          392.5      319.9      237.2      287.65

                      Share
                      of World
                      Exports

1     France          20.0%
2     Italy           19.0%
3     Spain           13.1%
4     United States   8.4%
5     Argentina       5.1%
6     Australia       3.8%
7     Germany         3.5%
8     South Africa    3.2%
9     Portugal        2.5%
10    Chile           2.2%
11    Romania         2.1%
12    China           2.0%
13    Hungary         1.6%
14    Greece          1.4%
15    Moldova         1.2%
16    Brazil          1.0%

Source: Rothfield, J., & Witter, G. 2008. The global wine statistical
compendium, 1961-2006

Table 2: Explanatory Variables

Variable       Endogenous/   Description
               exogenous

Bot/BulValue   Endogenous    Log of total value of bottled/
                               bulk wine exported
MarketPower    Endogenous    Log of Market Power Index
WineIndex      Endogenous    Log of Comparative Advantage Index
GDPpc          Exogenous     Log of Gross Domestic Product
                               per capita
ResPop         Exogenous     Log of Number of Researchers
                               per million people
ResExp         Exogenous     Log of Research and Development
                               Expenditures (% of GDP)
TechRD         Exogenous     Technicians in R&D per million people
RER            Exogenous     Log of real exchange rate index
Pop            Exogenous     Log of population

Table 3: GMM Econometric Model for Bottled Wine Export Market

Dependent Variable: Log of Exports of Bottled Wine

Variable                    Model 1      Model 2      Model 3

WineBotExp (t-1)            0.165 *      0.181 *      -0.012
                            (0.0923)     (0.0930)     (0.1195)
BotValue                    0.796 ***    0.806 ***    1.067 ***
                            (0.1453)     (0.1563)     (0.1158)
MarketPower                 -0.392 ***   -0.367 ***   -0.527 ***
                            (0.1168)     (0.1137)     (0.0912)
WineIndex                   -0.250 ***   -0.209 ***   -0.378 ***
                            (0.0881)     (0.0712)     (0.0368)
GDPpc                       -1.870 ***   -1.632 ***   -2.083 ***
                            (0.4375)     (0.3628)     (0.2770)
RER                         -0.764 ***   -0.899 ***   -0.895 ***
                            (0.2210)     (0.1705)     (0.2436)
Pop                         -0.157       -2.350       -4.013 **
                            (1.5133)     (1.430)      (1.8497)
TechRD
ResPop                                   0.319 ***    0.490 ***
                                         (0.1015)     (0.1113)
ResExp                      0.461 ***
                            (0.1448)
Constant                    22.194 ***   25.478 ***   32.567 ***
                            (4.9635)     (3.5052)     (5.4174)
Observations                88           84           49
Arellano-Bond test          1.137        1.718        1.002
[Prob.>z]                   0.25         0.09         0.32
Sargan test, [chi square]   104.138      97.435       42.538
[Prov>[chi square] ]        0.04         0.05         0.40

Table 4: GMM Economic Model for Bulk Wine Export Market Export

Dependent Variable: Log of Exports of Bulk Wine
Variable                    Model 1      Model 2      Model 3

WineBulExp (t-1)            0.121 *      0.033        0.116 *
                            (0.0708)     (0.0593)     (0.0621)
BulValue                    0.836 ***    0.967 ***    0.772 ***
                            (0.1781)     (0.2279)     (0.1679)
MarketPower                 -0.185       -0.206       -0.171
                            (0.1130)     (0.1951)     (0.1206)
WineIndex                   -0.253       -0.317       -0.348 *
                            (0.222)      (0.3155)     (0.1883)
GDPpc                       -0.656       -0.933       -1.280 **
                            (0.7130)     (0.9170)     (0.6116)
RER                         -1.569 ***   -1 247 ***   -1 431 ***
                            (0.4033)     (0.3384)     (0.3230)
Pop                         3.259        3.250        4.635 ***
                            (2.6861)     (5.4639)     (1.5991)
TechRD                                   0.205
                                         (0.2764)
ResPop                      0.053
                            (0.2378)
ResExp                                                0.586 ***
                                                      (0.1188)
Constant                    2.743        4.306        4.344
                            (11.236)     (22.0122)    (5.3234)
Observations                84           49           88
Arellano-Bond test          -1.449       -1.341       -1.797
[Prob.>z]                   0.15         0.18         0.07
Sargan test, [chi square]   92.975       48.894       95.923
[Prov>[chi square]]         0.09         0.19         0.11
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Author:Zhang, Pingying; Gallo, Andres; Baynard, Chris
Publication:Advances in Competitiveness Research
Article Type:Abstract
Geographic Code:4EUFR
Date:Jan 1, 2013
Words:6996
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