metadata: authors: 0: author: Dutz,Mark Andrew
1: author: O'Connell,Stephen A.
2: author: Troncoso,Javier Luis
count: Chile
docna: 0: docna: Public and private investments in innovation
            capabilities : structural transformation in the Chilean wine industry
docty: Policy Research Working Paper
theme: Other Private Sector Development,Analysis of economic growth
majtheme: Financial and private sector development,Economic management
subtopic: Adaptation to Climate Change,Private Sector Economics,Construction Industry,Common Carriers Industry,Food & Beverage Industry,General Manufacturing,Pulp & Paper Industry,Plastics & Rubber Industry,Hydrology,Food Security,Business Cycles and Stabilization Policies
teratopic: Science and Technology Development,Industry,Law and Development,Private Sector Development,Rural Development,Macroeconomics and Economic Growth,Agriculture
abstracts: cdata!: This paper assembles novel data on the
            Chilean wine industry to investigate the role of investments
            in knowledge capital on sales growth in domestic and
            international markets. The study uses archival data
            collected from the Government of Chile to compile and
            categorize public expenditures and programs supporting the
            Chilean wine industry over the period of 1990-2012 into
            investment in different types of knowledge capital. These
            spending categories are related to industry-level sales
            growth. The paper finds that the most important correlate is
            spending on research and development. The study also uses
            data from a new survey of Chilean wine firms to capture
            information on firm-specific investments in knowledge
            capital. The findings show that investments in collaboration
            capital, in particular hiring foreign consultants, as well
            as participation in international wine fairs are the
            strongest correlates of growth in export sales, while
            spending on aspects of branding (local advertising and brand
            design) are the strongest correlates of domestic market
            sales growth.
geo_reg_key: 119228,517191
repnme: repnme: Public and private investments in
            innovation capabilities : structural transformation in the
            Chilean wine industry
display_title: Public and private investments in
            innovation capabilities : structural transformation in the
            Chilean wine industry
listing_relative_url: /research/2014/07/19896099/public-private-investments-innovation-capabilities-structural-transformation-chilean-wine-industry
topicv3: Agriculture and Food Security m1326205 435,Public-Private Partnerships m1326334 2206,Manufacturing Sectors m1326521 1281,Water m1326522 137,Climate Change Adaptation m1327767 574
publishtoextweb_dt: 2014-07-01T00:00:00Z
historic_topic: Science and Technology Development,Industry,Law and Development,Private Sector Development,Rural Development,Macroeconomics and Economic Growth,Agriculture
no_of_pages: 43
author_keys: 0: author_key: 92214
1: author_key: 141960
2: author_key: 1210506
model_extractions: WPS6983 Policy Research Working Paper 6983 Public and Private Investments in Innovation Capabilities Structural Transformation in the Chilean Wine Industry _Mark A. Dutz Stephen D. O’Connell Javier L. Troncoso_ Trade and Competitiveness Global Practice Group July 2014
Policy Research Working Paper 6983

# **Abstract**

This paper assembles novel data on the Chilean wine industry to investigate the role of investments in knowledge capital on sales growth in domestic and international markets. The study uses archival data collected from the Government of Chile to compile and categorize public expenditures and programs supporting the Chilean wine industry over the period of 1990–2012 into investment in different types of knowledge capital. These spending categories are related to industry-level sales growth. The paper finds that the most important correlate is spending on research and development. The study also uses data from a new survey of Chilean wine firms to capture information on firm-specific investments in knowledge capital. The findings show that investments in collaboration capital, in particular hiring foreign consultants, as well as participation in international wine fairs are the strongest correlates of growth in export sales, while spending on aspects of branding (local advertising and brand design) are the strongest correlates of domestic market sales growth.

This paper is a product of the Trade and Competitiveness Global Practice Group. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The authors may be contacted at mdutz@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
**Public and Private Investments in Innovation Capabilities: Structural Transformation in the Chilean Wine Industry**

Mark A. Dutz, Stephen D. O’Connell, and Javier L. Troncoso<sup>1</sup> July 2014

**Keywords: Knowledge capital, intangible assets, innovation, productivity, economic growth JEL Codes: D24, O13, O14, O47, O31, O32, E22, L16, Q16**

> 1 GTCDR, The World Bank; City University of New York – Graduate Center; and Professor Emeritus, Universidad de Talca, respectively. The authors thank Charles Hulten for helpful comments, including the questions surrounding the accounting and synergies between public and private knowledge capital stocks raised in the concluding section. The authors gratefully acknowledge support from World Bank’s DEC Research Support Budget for financing aspects of the underlying empirical work.
# **I. INTRODUCTION**

The process of industrial development, resource reallocation and productivity dynamics can be decomposed into three complementary types of “structural transformation”, namely: (1) between-industry structural change, as inputs are reallocated across industrial activities; (2) within-industry structural change, as inputs are reallocated across enterprises within industries; and (3) within-firm structural change, as input reallocation and innovation within enterprises alters the structure and efficiency of the firm. Eichengreen, Park and Shin (2013) speculate that countries often face “middle-income traps” when productivity gains from between-industry structural change are largely exhausted and remaining gains are available primarily via more difficult-to-achieve within-firm structural change. In related work, Bollard, Klenow and Sharma (2013) decompose productivity dynamics in India into this three-way typology. They report that the large speed-up in the productivity of formal Indian manufacturing plants in the 1990s and early 2000s was mainly driven by within-plant productivity growth. Based on employment and productivity growth over the life cycle of Indian and Mexican manufacturing plants relative to the US, Hsieh and Klenow (2014) point to differences in within-plant productivity being more important than gains from resource reallocation across firms, plausibly accounting for about 25 percent of the gap in aggregate manufacturing total factor productivity between rich and poor countries.

This paper builds on a recent literature on “new sources of growth.” It directly measures key knowledgerelated elements of within-firm productivity in a developing country based on public and private investments in intangible assets, also referred to as knowledge capital (OECD 2013, Hulten 2013, Dutz 2013a). Measurement of business spending on knowledge capital is relatively recent, with seminal work applying direct expenditure methods initially done for the U.S. economy (OECD 1998, Nakamura 2001, Corrado, Hulten and Sichel (“CHS”) 2005, 2009). In contrast to the conventional approach of treating spending on knowledge assets as intermediate expenditures and thereby assuming that all their benefits are reflected in the current year’s output of tangible goods and services, the knowledge capital approach correctly capitalizes intangible outlays that contribute to production and value beyond the taxable year and treats them as longer-lived investments – using the same cost-based accounting that is used for physical capital. The knowledge capital approach expands the conventional proximate sources of growth beyond human and physical capital to include knowledge investments in the innovation and risk management capabilities of the enterprise. Importantly, these investments go significantly beyond traditionally-measured R&D expenditures to include a range of co-investments required for enterprises to decide what to produce and how, to develop new ideas, to execute and translate these ideas into products, processes, organizational changes and markets, and to manage associated risks. The CHS classification divides knowledge capital into three categories:<sup>2</sup> (1) **_digital assets_** _( “computerized information”) -_ software and databases (2) **_intellectual assets_** _(“innovative property”) -_ R&D, entertainment, literary and artistic originals (creative capital), architectural, engineering and other designs, new products and systems in the financial industry, and mineral exploration and evaluation (3 _)_ **_human-organizational assets_** _(“economic competencies”)_ - market research, advertising and brand equity (marketing capital), firm-specific human capital (worker skills and managerial capital),

> 2 Investments in risk management are here not conceptualized as a separate category of knowledge capital, but a consequence of appropriate investments in these three existing categories of knowledge assets. Risk management is a by-product of investments in these assets.

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organizational improvements and new business models (organizational capital) – and an additional-toCHS sub-category most important for businesses behind the global technological frontier, namely spending on collaboration-related assets to diffuse existing but new-to-the-firm technologies and adapt them to local context, such as outlays on networking and peer-to-peer learning from local clusters and global value chains, foreign buyers and sellers, consultants and study tours, and other forms learning through global networks (collaboration capital).

The acceleration of globalization, technological progress, and increased trade and competition have resulted in rents from new ideas becoming more important for sustained firm-level competitiveness and aggregate growth across countries (Canuto, Dutz and Reis, 2011). In addition, as countries accumulate larger stocks of human capital, the production and use of knowledge capital is both enabled and complemented. The increasing importance of knowledge capital over time is shown by the steady increase in the intangible investment rate in the US as a share of expanded nonfarm business output, from 8 percent in 1977 to 14 percent in 2010, in contrast with a secular decline in the tangible investment rate (Corrado and Hulten 2010, Hulten 2013).

A recent international empirical literature has highlighted investment in intangible assets both as a distinct category of firm investment and as a major driver of growth. In the US and the UK, firms now invest more in intangible than physical capital. Estimates of knowledge capital at the aggregate level across countries—to-date available for high-income OECD countries, Brazil, China and India—highlight that intangibles are an important and dynamic element of aggregate economic growth, with a significant positive correlation between investments in “core” knowledge capital (excluding software and architectural and engineering designs to control for the links with IT equipment investment and real estate bubbles) and PPP-adjusted output per capita (Hulten 2013). Applying this economy-wide methodology to Brazil, Dutz et al. (2012) estimate that during 2000-2008, annual business spending on intangibles averaged about 4 percent of GDP, showing that this investment is positively correlated with recent export growth and total factor productivity estimates across manufacturing industries. Hulten and Hao (2012) estimate China’s aggregate intangible expenditures at roughly 7.5 percent of GDP.

Measurement of investment in intangibles at the firm level is at an early stage for several reasons, though mainly because most national industrial surveys have not historically included the distinct questions needed to quantify investment in intangibles. This shortcoming of existing methods is being gradually addressed, but so far only for high-income countries: Haltiwanger, Haskel and Robb (2009) discuss new surveys piloted in the UK (as reported in Awano et al. 2010a, b) and in the US (based on new questions on spending on intangible assets by young firms added in the longitudinal Kauffman Firm Survey). They conclude that R&D is but one measure of knowledge investment: a range of additional questions are essential to fully capture knowledge spending, with complementary questions on depreciation rates of intangible assets yielding helpful insights.

The present study takes an initial step in measuring and quantifying the association between public and private investments in knowledge capital and industry-level and firm-level sales outcomes. It is the first study to take a close look at how knowledge capital works in a specific industry, where institutional details matter. In this paper, we empirically examine the linkages between intangible investments and industry- and firm-level exports in the Chilean wine industry. The study tests two hypotheses: (i) that 3
spending on knowledge capital is a statistically significant and economically important correlate of growth as reflected in exports, both at industry and firm levels; and (ii) that spending on reputation & branding and on learning through global collaboration and network-building, namely on connecting firms to better existing global technology flows, are both statistically significant and economically more important at the firm level than other types of knowledge capital.

Why focus on the wine industry? Based on an international comparison between Italy and three New World wine producers, namely Argentina, Chile and South Africa, Giuliani et al. (2011) explain why the wine industry (rather than electronics, software, pharmaceuticals or telecommunications) is an ideal industry to investigate technological catch-up in emerging countries, and how R&D and innovation are indeed the main drivers of an agro-food industry such as wine. They document how, as latecomers in the international market, New World producers have radically changed how wine is produced, sold and consumed. Their main argument is that product and process innovations, spurred by investments in innovation capabilities, have played a prominent role in the emergence of New World producers in the international market. Their empirical evidence shows that New World producers have improved the quality of their wines, investing in research in universities and laboratories, strengthening the link between university and industry, and importing external knowledge through experts. They show how a traditional agro-food industry can become highly competitive and catch up in the global market, thereby contributing significantly to the process of growth in these countries – when following a trajectory where investments in R&D and innovation play a prominent role. However, their empirical evidence is based largely on a set of case studies of universities and researchers, public institutions and firms in Argentina, Chile and South Africa. While there exist a number of other empirical studies on the wine industry (for Chile, see for instance Troncoso and Aguirre 2006, Kunc and Bas 2009, and Moreira, Troncoso and Bravo-Ureta 2011), there is no measurement of levels of investment in knowledge capital by firms or by the State—a shortcoming this study seeks to address.

We adopt two complementary methodologies. First, based on a unique data set on public and private knowledge capital investments compiled at the industry level, we categorize individual project expenditures from Government of Chile databases covering all innovation support programs targeted at the wine industry from 1990 to 2012 into different types of intangible assets. We then explore aggregate industry-level time series correlations between bottled wine exports and expenditures on main types of knowledge capital, lagged area planted, and a measure of global demand. Second, the paper reports on the findings of a novel field survey of wine enterprises, based on a specifically-designed “Survey of Investments in Knowledge Capital”, adapted to a developing country context and to the wine industry, and pre-tested in the field in Chile. Finally, we explore correlations between export or domestic bottled wine sales and expenditures on main types of knowledge and physical capital. In terms of methodology, the paper is most closely related to enterprise survey work undertaken by the Kauffman Foundation in the US as reported in Haltiwanger, Haskel and Robb (2009), and undertaken by Awano et al. (2010a, b) in the UK.

The paper makes four contributions to the literature. First, in terms of linkages with risk management, we illustrate how specific knowledge capital investments can be interpreted as supports to firms’ four pillars of risk management, adapted and extended to include innovation risk, based on a framework suggested for risk management by Ehrlich and Becker (1972): the resilience of development outcomes can be 4
improved both ex ante, before productivity or demand shocks are realized, by investing in knowledge, protection/enabling and insurance assets, and ex post by investing in coping/leveraging assets after the realization of the shock or after it becomes clear whether the innovation investments are succeeding or failing in the marketplace (Dutz 2013b). Second, at the industry level, the paper documents joint publicprivate investments across different types of knowledge capital. Total public-private co-investments over the period were sizeable. The strong statistically significant positive correlation of industry-level R&D outlays with bottled wine export sales suggests that investments in intangibles are more important for export competitiveness than an industry-level proxy for investments in tangible capital (area planted). The sizeable and long-term nature of public financing highlights the important role of government support to innovation, as outlined by Janeway (2012) and Mazzucato (2013). Third, the paper is, as far as the authors are aware, the first firm-level application of the knowledge capital approach to a developing country. Finally, in terms of measurement and policy guidance, the paper provides a survey design and analytical methodology for other industries, by quantifying the role of different types of knowledge assets in sales growth and suggesting what policies may matter for business competitiveness.

Section II provides a background to the Chilean wine industry and presents summary statistics on our industry- and firm-level datasets. Section III then presents linkages between investments in knowledge capital and risk management. It provides illustrative examples of how specific investments can be reinterpreted according to firms’ four pillars of risk management, as knowledge, protection/enabling, insurance, and coping/leveraging assets. Section IV presents linkages between knowledge capital investments and export (and domestic) sales, first based on industry-level data and then based on firmlevel data. The final section concludes and discusses questions for further research.

# **II.1. STRUCTURAL TRANSFORMATION IN THE CHILEAN WINE INDUSTRY**

The Chilean wine industry has experienced impressive growth in recent decades. As highlighted in Figure 1a, growth in total wine production increased from 187 to 1,255 million liters between 1990 and 2012—at an average compound annual growth rate of 9.0 percent. During this same time, total area planted with wine grapes increased from 65.2 to 127.0 thousand hectares (3.1 average CAGR).<sup>3</sup> By decomposing this growth rate into two periods, it is evident that the decade of the 1990s saw a faster compound annual growth rate in production of 13.1 percent (from a lower initial base) relative to the subsequent 2000-2012 period of 5.7 percent growth per annum. Total wine exports and the subset of total bottled wine exports,<sup>4</sup> in turn, grew from 43 and 23 to 744 and 406 million liters over the same period, at compound annual growth rates of 13.8 and 14.0 percent respectively. Faster rates of growth of wine exports relative to wine production reflect a gradual shift in sales from domestic to export markets over time. Chile has climbed to be among the top five countries in terms of national shares of world wine export volume and value by the late 2000s (behind France, Italy, Spain and Australia, but ahead of the US, Germany, New Zealand, Argentina and South Africa, among others) (Andersen and Nelgen 2011).

> 3 Area planted excludes the area with table grapes. As capital investment is closely related to area planted, this variable can also be used as a proxy of investments in physical capital.

> 4 Bottled wine exports include tariff codes 22042110 (wines with Denomination of Origin) and 22041000 (sparkling wines), and exclude codes 22042190 (wine in tetrapack equal to or less than 2.0 litres) and 22042990 (other wine, mainly larger bulk containers). The series were obtained from ODEPA, Ministry of Agriculture’s Office of Agrarian Studies and Policies.

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**Figure 1a: Evolution of export volumes, 1990 to 2012**

<!-- Start of picture text --> 1,400<br>1,255<br>Total wine production<br>1,200<br>All wine exports<br>1,000 Bottled wine exports<br>800 743.9<br>600<br>405.8<br>400<br>200 187<br>43.1<br>0 22.7<br>MM Litres<br>1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012<br><!-- End of picture text --> The increase in export volumes between 1990 and 2012 is mirrored by equally spectacular increases in export values<sup>5</sup> : from $116 million to $1.78 billion for total wine exports (or 13.2 percent per annum, 23 percent per annum over the 1990s and 5.6 percent per annum thereafter), and from $89 million to 1.35 billion for bottled wine exports (or 13.1 percent per annum, again 23 percent per annum over the 1990s and 5.5 percent per annum thereafter). Figure 1b shows the evolution of export unit values over time, with a significant price premium for bottled wine over all wine exports (taking into account that the highervalue bottled wine exports are also included in total exports). However, it is striking that bottled wine unit values have not increased further over time, suggestive of the continuing predominant niche of most Chilean wines as relatively low-cost “value for money” products. Figure 1b also shows, on the right axis, the evolution of the share of bottled wine exports in total exports by volume over time, with the share remaining relatively constant at approximately 55 percent, with a low of 39 percent in 1994 and a high of 61 percent in 2011 – highlighting that the mix of export volumes has not shifted significantly toward higher-value wines.<sup>67</sup>

> 5 All figures throughout the study are reported in constant (2012) US dollars, unless otherwise noted.

> 6 The share of bottled wine exports has also remained fairly constant over time, beginning the period at 77 percent in 1990 and ending at 76 percent in 2012, with a low of 67 percent in 1993 and a high of 82 percent in 2007.

> 7 As a signal of what is possible and the global brand image that Chile has attained, Concha y Toro has consistently been rated in the top 3 most valuable wine brands in the world from 2006 through 2013, according to an annual compilation of the top 100 spirits and wine brands (Intangible Business). These global rankings are based on objective measures such as market share, brand growth, price positioning, and number of markets with a significant brand presence, together with a range of subjective measures.

6
**Figure 1b: Evolution of export unit values and bottled wine share of exports, 1990 to 2012**

<!-- Start of picture text --> $6.00 70%<br>60%<br>$5.00<br>53% 55%<br>50%<br>$4.00<br>$3.95<br>40%<br>$3.00 $3.33<br>$2.69 30%<br>$2.39<br>$2.00<br>20%<br>$1.00 USD per Litre, Bottled wine exports 10%<br>USD per Litre, All wine exports<br>Bottled wine export share (% volume, right axis)<br>$0.00 0%<br>2012 USD per Litre<br>Bottled wine share of exports<br><!-- End of picture text --> This evolution of the Chilean wine industry was accompanied by significant structural transformation including innovations both in plantations and wineries as well as in the management of firms. The area planted increased substantially in the 1990s and 2000s, and the proportion of traditional cultivars (e.g.’Pais’ or Mission) was reduced to the advantage of finer varieties; also vine training systems and pruning methods were improved and wine cellars evolved from traditional winemaking methods (based on fermentation in oak casks) to modern oenological technology using stainless steel vats and equipment. In all these transformations, an important role was played by renowned winemaking companies from other countries, as Miguel Torres Vineyards (Spain), Pernod Ricard or Rothchild-Lafitte (France), Kendall Jackson (U.S.A) and Mildara Blass (Australia), that invested in Chile or developed joint ventures with local wineries (Vergara, 2001). These structural transformations required investments not only in physical capital but also in worker and management training, adaptive R&D, software (including software to manage oenological processes, such as Kupay, developed by the Chilean firm, SONDA), new organizations (e.g. Wines of Chile A.G, with branches in the U.K and the U.S), trademarks recognized in Chile and abroad, and many other intangible investments.

# **II.2 INDUSTRY-LEVEL DATA**

The extent of public sector funding support to intangible investments in the Chilean wine industry was sizeable, sustained, multi-faceted, and growing over 1990-2012. Table 1 shows the magnitude of this funding by knowledge capital type and program funding source, disaggregated into public funding and co-financing by private beneficiaries.<sup>8</sup> Public support and matching private contributions amounted to a

> 8 Although public funds are supplied to the wine industry by several governmental programs, FIA ("Fondo de Innovación Agraria" of the Ministry of Agriculture) is charged with keeping a record of the research projects funded with public resources to avoid duplications. FIA provided us with a complete list of the research projects carried out for the wine industry in the period 1990 through 2012, including the funds committed from public and private sources CORFO provided data on remaining public-private support to the different types of knowledge capital.

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sizeable total of $120 million, with $87.8 million or 73 percent of the total accounted for by public funding.

Across the different types of knowledge capital receiving public support, R&D projects received by far the largest total support, $79.3 million, and also benefited from the largest share of public support, $59.9 million or over 75 percent of the R&D total. The main public R&D funding source was CORFO, the Chilean Economic Development Agency<sup>9</sup> , through its different support programs: INNOVA CHILE, a new agency formed in 2005, and merging the FONTEC program (the National Productivity and Technological Development Fund, created in 1991 to increase local industry competitiveness by supporting technological innovation) and the FDI program (the Innovation Development Fund). The other main funding sources were two-fold: first, CONICYT, the Chilean National Research Council, through FONDEF (the Science and Technology Development Fund, created in 1991 to support public-private partnerships between public research organizations and private firms to work together on R&D projects) and FONDECYT (the National Fund for Scientific and Technological Development, created in 1981 to fund basic scientific and technological research); second, the Ministry of Agriculture, through FIA (the Foundation for Agrarian Innovation to fund innovation in agricultural industries) and SAG (the Agriculture and Livestock Service, supporting agriculture development through improvements in the health and vigor of animals and plants).

Training projects received the next largest public support, $16.1 million or 77 percent of the total recorded public-private funding for training of $20.9 million. Public support for worker training and certification picked up significantly in the 2000s with the public subsidy offered through the Ministry of Labor and Social Security’s SENCE program (National Training and Employment Service), which provides a profit tax exemption to firms availing themselves of approved training. For wine firms, SENCE funding was provided largely through OTIC Chile Vinos, an “Intermediary Technical Training Organization” set up by the Vinos de Chile enterprise association. CORFO was another important public funder of training support projects, both directly and through INNOVA CHILE.

> 9 CORFO, the Spanish acronym of the Corporacion de Fomento de la Produccion de Chile, is a government agency dedicated to promote entrepreneurship, innovation and economic growth since 1939. CORFO reorganized in 1991, transferring its loan portfolio to the private banking system, and refocused on reducing market failures impeding development, in particular through technology and innovation policy and project support.

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**Table 1: Total public and private funding of knowledge capital, 1990-2012 (in MM 2012 USD)**

|**Type and Funding Source**|**Public**<br>**Funding**|**Co-financing by**<br>**beneficiaries**|
|---|---|---|
|**_R&D_**|**_59.87_**|**_19.45_**|
|_INNOVA CHILE_|21.77|12.18|
|_FONDEF_|16.31|-|
|_FIA_|5.87|-|
|_FONTEC_|5.62|4.66|
|_FDI_|4.16|2.61|
|_FONDECYT_|3.90|-|
|_SAG_|2.25|-|
|**_Training_**|**_16.06_**|**_4.82_**|
|_SENCE/ Vinos de Chile - OTIC_|9.42|-|
|_CORFO_|3.72|2.97|
|_INNOVA CHILE_|2.92|1.85|
|**_Joint Marketing Support_**|**_6.14_**|**_5.81_**|
|_CORFO_|5.38|4.61|
|_INNOVA CHILE_|0.77|1.19|
|**_Global Collaboration_**|**_4.57_**|**_1.91_**|
|_CORFO_|2.45|-|
|_INNOVA CHILE_|2.12|1.91|
|**_Market Research_**|**_0.21_**|**_0.14_**|
|_CORFO/ INNOVA CHILE_|0.21|0.14|
|**_Business Process Improvement_**|**_0.98_**|**_0.75_**|
|_CORFO_|0.73|0.46|
|_INNOVA CHILE_|0.25|0.29|
|**_Total_**|**_87.83_**|**_32.88_**|

The other main types of knowledge capital receiving public support were funded either directly by CORFO or through INNOVA CHILE. Joint marketing support projects benefited from over $6 million in public funding, with matching private sector funding of almost as much ($5.8 million). Over half of these support projects (74 of 133 projects) were listed as PROFOs or “Associative Promotion Projects”, a program created in 1992 managed by CORFO which promoted associations among groups of small and medium enterprises (SMEs), requiring the participation of at least five SMEs to improve technical, financial, managerial and marketing capabilities. In the wine industry, most PROFOs were directed at marketing challenges such as conquering new international markets. Rivas (2012) describes the case of SME wineries that initially produced and sold bulk wine to larger wine firms, and as a result of the program learned to work together to upgrade quality and jointly market own exports directly to global markets.

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Global connectivity and knowledge network-building support projects were largely funded from public sources, with $4.6 million or over 70 percent of total public-private funding for these types of learning funded by CORFO. Approximately 60 percent of these projects were “misiones de captura tecnologica” or technology capture trips, for instance a structured study tour to France to learn about the latest technologies for the production of biodynamic wines, or a tour to Australia to learn “about the technologies used by one of our main global competitors”. Roughly 20 percent of the projects were “consultoria especializada” or foreign consultant services. And the remaining 20 percent were projects from a program involving the diagnosis of problems of a particular productive chain and the collaborative solution to such problems that typically included expert consultancies to help upgrade outdated technologies. Finally, market research projects were predominantly labeled “Programa de prospección e investigación de mercados”, and were typically supporting the national wine associations in their projects to better understand evolving foreign buyer wine tastes. Business process improvement (BPI) projects were predominantly support to enterprises’ upgrading with respect to the ISO 9000, 14000 and HACCP (Hazard Analysis and Critical Control Points for food safety) series product process improvement methodologies.

Figure 2 shows the available data on programmatic funding to the Chilean wine industry by knowledge capital type and source. The data are disaggregated on a year-by-year, project, and public-private funding basis. The figures on the bars refer to the number of distinct projects that were active in a given year (a project may be firm-specific, as in BPI support, but typically benefit a group of firms, as in a PROFO project, or eventually most firms in the industry, as in a typical global connectivity or R&D support).

Support for R&D has been the most continuous on a year-by-year basis over the 1990-2012 period. It began with a single support project disbursing $8,000 in 1990, rose to disbursements of $200,000 over 4 projects by 1995, to $5.7 million over 23 projects in 2000, and to a high of $8.3 million over 35 projects in 2010. Public support for most other types of knowledge capital investments began only later, with support for training beginning in 1996, for global collaboration in 1998, and with support for joint marketing, market research and business process improvement only beginning in 2005.

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**Figure 2: Funding amounts by knowledge capital type and source, 1990-2012**

|1.2<br>**Global Collaboration**|**Business Process Improvement**<br>0.7|
|---|---|
|**8**<br>**8 16**<sup>**16**</sup><br>**10**<br><br>0.6<br>0.8<br>1|**55**<br>**19**<br>0.3<br>0.4<br>0.5<br>0.6|
|**2**<br>**1**<br>**2**<br>**1**<br>**5**<br>**4**<br>**6**<br>**~~1~~**<br>**1**<br>0<br>0.2<br>0.4|**2**<br>**34**<br>**28**<br>**27**<br>**18**<br>**~~11~~**<br>0<br>0.1<br>0.2|
|**21**<br>**19**<br>**23 20**<br>**13**<br>**18**<br>**15**<br>**~~4~~**<br>0<br>0.5<br>1<br>1.5<br>2<br>2.5<br>3<br>**Joint Marketing Support**|**1**<br>**2**<br>**2**<br>0<br>0.02<br>0.04<br>0.06<br>0.08<br>0.1<br>0.12<br>0.14<br>0.16<br>0.18<br>0.2<br>**Market Research**|
|**1**<sup>**~~1~~1 **</sup><br>**13**<br>**17**<br>**25**<br>**25**<br>**31 44**<br>**25**<br>**9**<br>0<br>0.5<br>1<br>1.5<br>2<br>2.5<br>3<br>3.5<br>4<br>4.5<br>**Training**|**1 2 2**<sup>**3 3 4**</sup><sup>**~~3 8~~**</sup><br>**11**<br>**20**<sup>**23**</sup><br>**27**<br>**28**<br>**27**<br>**39**<br>**36**<sup>**29**</sup><br>**26**<br>**33 32**<br>**35**<br>**23**<br>**19**<br>0<br>1<br>2<br>3<br>4<br>5<br>6<br>7<br>8<br>9<br>**R&D**<br>Public Financing<br>Co-financing by<br>beneficiaries|
|1990<br>1992<br>1994<br>1996<br>1998<br>2000<br>2002<br>2004<br>2006<br>2008<br>2010<br>2012||

_Note: All figures in 2012 USD (MM). Series labels indicate number of distinct funded projects in the category and year._ 11
# **II.3 FIRM-LEVEL DATA**

Between January and April 2013, we collected firm-level information on investments in physical and intangible assets, export and domestic sales, estimated lifespan of intangible assets, and other firm characteristics of a stratified sample of firms in the Chilean wine industry for the three latest available years (2009 through 2011).<sup>10</sup> In particular, the questionnaire included novel, detailed questions on spending (both in-house and purchased through external providers) on the six main types of intangible assets—software, R&D, design, reputation & branding, training and business process improvements— plus collaboration-related economic competencies (collaborative learning through spending on both foreign consultant services and technology capture trips<sup>11</sup> ).<sup>12</sup>

**Table 2. Chilean wine industry: Universe and sample**

|**Size strata(ha)**|**Uni**<br>No.|**verse**<br>%|**Su**<br>No.|**rvey**<br>%|
|---|---|---|---|---|
|x≤100|120|50.8|9|37.5|
|100<x≤500|83|35.2|8|33.3|
|500<x≤2,000|29|12.3|3|12.5|
|x>2,000|4|1.7|4|16.7|
|**Total**|**236**|**100**|**24**|**100**|

The sample frame was drawn from a database of all registered wine-producing enterprises. Table 2 shows the total number of firms in the Chilean wine industry as of end-2011 and the respondent sample according to firm size (proxied by production hectares). As is evident, the stratum of smallest firms (100 hectares and less) is under-represented in the sample, while the largest firms were intentionally oversampled. Initially the identified, intended sample included 50 firms, weighted proportionally to the population, but the survey period coincided with harvest time in the vineyards and many firm managers did not make themselves available to be surveyed.<sup>13</sup> Thus, only 24 firms (or 48 percent of the original sample) responded the questionnaire. In total, the firms sampled represent 53-54 percent and 56-60 percent of Chilean wine exports between 2009 and 2011, measured in export value and physical output, respectively.

Figure 3 shows the incidence of spending by aggregated intangible asset type, broken down by size group (less than versus more than 500 hectares). Our results are similar to what Awano et al. (2010) found for the UK across all industries, namely that the top three asset types were training, software, and reputation & branding, and that R&D had the lowest incidence – with results holding for both large and small

> 10 The survey instrument used is available in the Appendix. It is a new survey instrument, adapted from the “Investment in Intangible Assets” survey sent to 2,004 UK firms by Awano et al. (2010), which in turn was modified from a template provided by the Central Bureau of Statistics in Israel. Two surveyors visited the sampled firms to apply the questionnaire.

> 11 These were typically structured study tours with local entrepreneurs going abroad.

> 12 The questionnaire is attached in the Appendix.

> 13 There is no indication that the respondents represented a biased sample. Awano et al. (2010) report that 42 percent of firms to which their survey was sent provided knowledge capital spending information.

12
firms.<sup>14</sup> Our results confirm that non-R&D intangible spending is much more widespread than outlays on R&D. As in the UK, the average benefit lives for each asset category are greater than one year, strongly supporting the case for capitalizing the assets. Interestingly, our newly-tracked knowledge capital category, spending on learning from global collaboration, is as common as software for smaller firms (71% of firms investing) and as important as design and business process improvements for larger firms (19% of firms investing).

**Figure 3: Share of firms engaging in knowledge capital investment, by type and size**

<!-- Start of picture text --> Share of firms engaging in KBC investment, by type and size<br><500 ha<br>Chilean Wine industry (sample) >500 ha<br>1.2<br>1<br>0.8<br>0.6<br>0.4<br>0.2<br>0<br>Any Training Any Software Any Reputation Any R&D Any Design Any Business Any Global<br>/ Branding Process Collab.<br>Improvements<br><!-- End of picture text --> Figure 4 shows average expenditure on each asset type conditional on reporting positive spending, again broken down by size group, for 2011. There are large differences in the average expenditure by asset types and across size classes. In particular, large firms report spending significantly higher spending levels on average than smaller firms for the three most common asset types by incidence, namely reputation & branding, software and training. Spending is especially high for the largest firms on reputation & branding (an average of $771,000), driven by high levels of spending on creating and maintaining brands by the largest firms that are active and need to pay trademark licensing costs in a large number of foreign export markets.<sup>15</sup> Spending is also significantly higher on training for the larger than for the smaller firms ($174,000 versus $15,000). Interestingly, reported average spending on R&D, business process improvements, and learning through global collaboration is higher for the smaller than for the larger firms. This may be due to a number of reasons, including a possible reluctance of the largest firms to reveal their actual spending in these categories as these may be perceived to be important sources 14 Note that among the top three asset types, the results for the Chilean wine industry are distinct from those across all industries in the UK, with in Chile reputation & branding being the most common asset type (with all large firms, and 96% of smaller firms investing), followed by software (76% of large and 71% of smaller firms investing) and then training (67% of large and 78% of smaller firms investing); the incidence of R&D spending is 8% for small and 5% for large firms. In the UK training was the most common asset type (70% of large and 34% of smaller firms investing), followed by software (57% of large and 30% of smaller firms) and reputation & branding (38 and 22% respectively); the incidence of R&D spending was 8% for small and 19% for large firms. This result is no doubt affected by the importance of reputation and branding for the global wine industry.

> 15 In 2011, Concha y Toro purchased California’s Fetzer Winery for US$ 238 million, adding significantly to its brand portfolio. However, this is not an exceptional outlier, as the other largest firms also spend significantly more than the smaller firms in this asset category.

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of comparative advantage; as well, especially on R&D, the larger firms may participate mainly through collaborative public-private initiatives as reflected in the industry-level data, or larger firm respondents may systematically have a more restricted view of what is included under the R&D category.

**Figure 4: Mean knowledge capital investment levels, by type and size**

<!-- Start of picture text --> 771<br>200 <500 ha<br>180<br>>500 ha<br>160<br>140<br>120<br>100<br>80<br>60<br>40<br>20<br>0<br>Thousands USD<br><!-- End of picture text --> In addition to the magnitude of spending, the survey asked respondents to estimate the number of years that an investment in a particular asset category would continue to yield benefits. Figure 5 shows the average estimated benefit lives for each asset type (except for investments in global collaboration). Again, there are similarities between the Chilean wine industry and UK industries: training is the asset type with the shortest reported asset life, namely 2.1 years in Chile and 2.7 years in the UK. While R&D was the asset type with the longest reported benefit life in the UK (4.6 years), it was in second place in Chile, with an average asset life of 5.3 years. Interestingly, the asset type with the longest reported asset life in the Chilean wine industry is reputation & branding, with an average benefit life of 9.9 years – a testament to the perceived staying power in the minds of consumers of well-established wine brands. Most importantly, as in the UK, the average life lengths across all assets types are comfortably greater than one year, strongly supporting the case for capitalizing knowledge capital assets.

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**Figure 5: Mean reported life of knowledge capital assets**

<!-- Start of picture text --> 20<br>15<br>10<br>5<br>0<br>-5<br>Training Software Branding R&D Design BP<br>Improvements<br><!-- End of picture text --> _Note: Error bars represent 95% confidence intervals._

**III. LINKAGES BETWEEN KNOWLEDGE CAPITAL INVESTMENTS AND RISK MANAGEMENT**

In addition to being an important source of total investment and growth, different types of enterprise investments in intangibles also can play a critical role as investments in enterprises’ pillars of risk management, providing enterprises with essential capabilities to anticipate, absorb and adapt to exogenous risks, and undertake risky activities in pursuit of larger expected profits with higher probabilities of success – empowering firms to learn and execute as enabled information platforms.<sup>16</sup> The main types of intangible investments can be mapped into the four pillars of risk managed initially proposed by Ehrlich and Becker (1972) (see Figure 6):<sup>17</sup>

- Investments in **_knowledge_** of supply and demand trends and the likelihood of shocks, including changes in existing and emerging global technologies and changes in consumer preferences. This includes expenditures on R&D and global connectivity (including investments in knowledge diffusion networks and various search and match mechanisms to learn from and co-create with other local firms, global corporate partners, suppliers and buyers, universities and the diaspora).

- Investments in **_protection/enabling_** to reduce the probability of losses and increase the likelihood of successful input reallocation and innovation. This includes expenditures on market research, branding and advertising to expand product varieties and market reach and thereby diversify location-specific product risks both on production and demand sides. The optimal reallocation of resources under uncertainty may not be to invest all into a high-risk new technology, but to invest some resources in the existing technology and benefit from the option value of waiting until some additional

> 16 See Hulten (2013) on some policy implications of conceptualizing the firm as an information platform.

> 17 Sheffi (2005) surveys a wide range of intangible investments that firms have made to increase knowledge, selfprotect, insure against, and cope with low-probability high-impact disruptions, broken down into “reducing vulnerability” (early detection and security investments in databases and software to reduce the likelihood of intentional disruptions from industrial actions, sabotage or terrorism), “building resilience through redundancy” (investments in slack, non-used inventory, capacity and IT systems, and increased holdings of retained earnings) and “building resilience through flexibility” (investments in new business models to allow interchangeability of plants, parts and people, realign supplier relations in supply chains, and modify internal culture towards greater safety, quality, continuous communications, and conditioning for disruptions).

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<!-- Start of picture text --> KNOWLEDGE<br>EX ANTE of Supply/Demand trends<br>LA & likelihood of shocks . Se<br>PROTECTION/ENABLING RISK : duce cue oF<br>to reduce probability of BUSES ae eA een ee<br>losses & increase likelihood MANAGEMENT by transferring fecetlasse<br>of successful innovations from good to bad times<br>WS COPING/LEVERAGING P|<br>Ry for loss recovery, or Ss<br>EX POST benefit enlargement if<br>innovations are successful<br>in marketplace<br><!-- End of picture text -->
<!-- Start of picture text --> ~~ TM<br>n y,<br>ee<br>, aaa 2.<br><!-- End of picture text -->
# Examples of investments in knowledge capital that support enterprise risk management include:

(i) **Investments in knowledge** . An example of expenditures on knowledge related to changing global technologies and effectively adjusting to the risk of losing market share when foreign competitors innovate is Miguel Torres’ (a Spanish-owned FDI firm) first introduction in Chile of temperaturecontrolled stainless steel vats (in widespread use in high-income countries by then). They replaced the traditional concrete fermenting vats that did not allow temperature control and that retained residues adversely affecting taste and smell. This led Chilean-owned vineyards to introduce them – and required additional investments in technical support and local learning, as no one in Chile knew how to assemble them. To further lower the risk of falling behind the evolving technological frontier, CORFO and participating enterprises co-invested $5.1 million between 2005 and 2010 in 48 “technology capture” foreign trips and in 15 “foreign consultant service engagements” by oenologists, viticulturalists and other global experts. And to lower the risk of volatile exports for smaller producers with less widespread distribution networks as well as to increase export levels, CORFO’s PROFO program and participating enterprises co-invested $11.5 million between 2005 and 2010 in a range of initiatives to learn how to best promote local wine regions. Through these investments, they developed a ready buyers’ market and strengthened customer loyalty, reducing demand volatility by making it more price-inelastic.

(ii) **Investments in protection/enabling** . Chile’s ideal geographical isolation (desert in the North, mountains to the East, Antarctic to the South, and Pacific to the West) has historically protected it from viticulture hazards such as the phylloxera louse. To protect this natural low-risk factor underpinning its agricultural competitiveness, Chile’s government, through its Agriculture and Livestock Service (SAG), invested in rigorous zoo- and phyto-sanitary border control. An example of knowledge capital expenditures to protect vine production against disaster risks such as pests and diseases as well as climate change-induced drought and temperature variability is the co-investment of $1.2 million between 2004 and 2012 by FONDEF. The co-investment financed a major study on adapting root stock and cultivar grafting to local conditions, generating the know-how to graft local vines on North American grapevine rootstocks and thereby provide resistance to parasites. It also ensured local adaptation to changing water and temperature conditions, helped regulate the vigor of vine foliage to changing external conditions, and allowed lower-cost adaptation to changing soil salinity conditions. Other protection against increasing drought (as melt-water from the Andes diminishes) was provided by investments in drip irrigation, which also enables more precise computer control of both watering and fertilizer, but required complementary investment in worker training.

(iii) **Investments in insurance** . An example of insurance-related expenditures on knowledge capital is an investment in 2003 in a detailed census of all winemaking enterprises to document and benchmark their existing storage capacity. This stimulated investment in storage capacity as a shock absorber of volatile world wine prices together with exchange rate risk – allowing smoothing of export supply to markets depending on varying earnings potential from year to year. Investment in additional storage capacity also serves as insurance against the risk of loss of product from leaking vats as a result of unpredictable earthquakes, minimizing the marketing risks associated with foreign customers not being assured of continuous de livery of product and possibly switching to other countries’ product. Finally, an example of expenditures on knowledge capital to insure against the risk of further appreciation of the exchange rate is 18
the co-investment of $725,000 between 2008 and 2011 by FIA and participating enterprises in R&D and an economic evaluation of sparkling wine based on a traditional low-value grape variety (Pais, or Mission in California) – which dramatically lowered the local cost of producing a good-quality sparkling export wine.

(iv) **Investments in coping/leveraging** . An example of expenditures on coping/leveraging-related knowledge capital is the $15.3 million joint public-private investment in training between 2005 and 2010 to upgrade worker skills by introducing them to increasingly sophisticated vineyard farming and winemaking techniques.

# **IV. LINKAGES BETWEEN KNOWLEDGE CAPITAL INVESTMENTS AND EXPORTS**

# **IV.1 INDUSTRY-LEVEL ANALYSIS**

We hypothesize that higher investments in knowledge capital over time are associated with higher exports, controlling for investments in physical capital (proxied by vine area planted) and external demand (proxied by average GDP per capita of main wine purchasing countries). To motivate the regression analysis, Figure 9 presents a scatter plot of the logged values of wine exports and R&D spending across the entire Chilean wine industry for our period of study.

**Figure 9: Scatterplot of ln[R&D spending] and ln[Export Values] (1990-2012)**

<!-- Start of picture text --> 2012<br>2011 2022 0700802 0 910<br>2003200520062004<br>2002<br>2001<br>2000<br>1999<br>1998<br>1997<br>1996<br>1995<br>1992 19941993<br>1991<br>1990<br>-4 -2 0 2<br>ln(R&D in MM USD)<br>8<br>7<br>6<br>ln(exports in MM USD)<br>5<br>4<br><!-- End of picture text --> Figure 9 highlights a strong time-series trend among both export values and R&D spending. Interestingly, a sharp reduction in R&D spending in 2011 and 2012 coincides with almost no increase in exports between 2010 and 2012. Since this shows a strong time-series component, we check whether one of our main control variables, area planted, is also correlated to exports in a similar way in Figure 10. Area planted (in natural log) also has a strong time-series component; a concern is thus that the effect of R&D (or other knowledge capital variables) may just capture correlations with other determinants of exports.

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**Figure 10: Scatterplot of ln[Area planted] and ln[Export Values] (1990-2012)**

<!-- Start of picture text --> 2012<br>2008 2009 20102007 2011<br>2003200420052006<br>2002<br>2001<br>2000<br>1999<br>1998<br>1997<br>1996<br>1995<br>1994 19931992<br>1991<br>1990<br>4 4.2 4.4 4.6 4.8<br>ln(Area Planted ha.)<br>8<br>7<br>6<br>ln(exports in MM USD)<br>5<br>4<br><!-- End of picture text --> A plot of residuals in Figure 11 of exports and R&D (after controlling for area planted) suggests that even once area planted is controlled for, there is a strong relationship between R&D and exports. Thus even after controlling for important input factors that appear similarly correlated such as area planted, R&D spending appears to remain an important determinant of export values.

**Figure 11: Residuals scatterplot of ln[R&D spending] and ln[Export Values] (1990-2012) controlling for Area Planted**

<!-- Start of picture text --> 1996<br>1997<br>1998<br>2008<br>1995<br>20091994 1999<br>2012 20072010<br>20032004<br>2011 2001200620052002<br>2000<br>1993<br>1992<br>1991<br>1990<br>-4 -2 0 2<br>ln(R&D in MM USD) - residuals<br>Residuals Fitted values<br>Fitted values - excl 2011+<br>.5<br>0<br>-.5<br>ln(exports in MM USD) - residuals<br>-1<br><!-- End of picture text --> We now investigate the association between aggregate industry-level exports and joint public-private spending on knowledge capital via multivariate OLS regression. Our estimation approach includes values of bottled wine exports, the public policy-supported aggregated intangible expenditure types (R&D, 20
reputation & branding, training, and global connectivity) and two controls (area planted and a populationweighted average GDP per capita across the US, Canada, EU countries, and China to proxy for international demand). All variables are in natural logs. We vary specification choices over aggregated versus more disaggregated knowledge capital types, with separate regressions for increasing years for different lagged specifications for the area planted variable (as current-year planted area likely is only associated with exports in subsequent years, with a typical three-year or even four-year period before new vine seedlings become productive and generate bottled wine).<sup>20</sup> The results of these estimations are in Tables 3 and 4.

**Table 3: Association of knowledge capital aggregated by type with industry-level exports**

||(1)|(2)|(3)|(4)|(5)|(6)|
|---|---|---|---|---|---|---|
|_Export output (natural log):_|**Value**|**s in 2012**|**USD**||**Litres**||
|_Areaplanted lag:_|Current|2yrs|4yrs|Current|2yrs|4yrs|
|Area Planted|-0.157|0.098|0.165|-0.645+|-0.473|-0.094|
||(0.313)|(0.330)|(0.415)|(0.315)|(0.358)|(0.482)|
|R&D|0.150+++|0.161+++|0.161+++|0.133++|0.126++|0.150++|
||(0.048)|(0.051)|(0.050)|(0.048)|(0.055)|(0.058)|
|Training|0.219|0.160|0.150|0.203|0.122|0.051|
||(0.139)|(0.129)|(0.134)|(0.140)|(0.139)|(0.156)|
|Business Processes|-0.012|-0.006|-0.006|-0.000|-0.004|0.010|
||(0.036)|(0.037)|(0.036)|(0.036)|(0.040)|(0.042)|
|Reputation & Branding|-0.172|-0.153|-0.158|-0.112|-0.052|-0.041|
||(0.116)|(0.112)|(0.112)|(0.117)|(0.121)|(0.130)|
|Global Collaboration|0.019|0.004|0.007|-0.044|-0.024|-0.063|
||(0.044)|(0.052)|(0.045)|(0.044)|(0.056)|(0.052)|
|GDP Per Capita|2.120|1.885|1.931|2.842|3.963+|2.939|
|(weighted average)|(1.848)|(2.021)|(1.914)|(1.860)|(2.192)|(2.225)|
|R-sq|0.994|0.994|0.994|0.993|0.992|0.991|

_Specifications have 23 observations and include an unreported constant term. Standard errors in parentheses. + p<0.1, ++ p<.05, +++ p<.01_ In Table 3, the only aggregate knowledge capital type that is statistically significantly positively correlated with bottled wine exports over time is R&D spending (at the 1% level). For R&D, the coefficient is relatively stable across the different lag periods, suggesting that a 10 percent increase in R&D expenditures is correlated with a 1.5-1.6 percent increase in export values, and a 1.3-1.5 percent 20 We dummy out missing observations for the few cases in which our time series data do not extend to the beginning of analysis period.

21
increase in volumes. Note that the elasticity of R&D is higher for value than for volume, which suggests a positive effect of R&D on price and consumer satisfaction.

**Table 4: Association of knowledge capital disaggregated by type with industry-level exports**

||(1)|(2)|(3)|(4)|(5)|(6)|
|---|---|---|---|---|---|---|
|_Export output (natural log):_|**Value**|**s in 2012**|**USD**||**Litres**||
|_Areaplanted lag:_|Current|2yrs|4yrs|Current|2yrs|4yrs|
|Area Planted|0.095|0.200|0.204|-0.453|-0.366|0.010|
||(0.392)|(0.382)|(0.490)|(0.366)|(0.368)|(0.490)|
|R&D|0.118++|0.125++|0.120++|0.106++|0.108++|0.132++|
||(0.049)|(0.049)|(0.047)|(0.046)|(0.047)|(0.047)|
|Training|0.013|-0.004|-0.006|0.044|0.012|-0.060|
||(0.124)|(0.113)|(0.131)|(0.116)|(0.109)|(0.131)|
|Business Processes|-0.029|-0.025|-0.029|-0.012|-0.005|0.012|
||(0.040)|(0.038)|(0.035)|(0.037)|(0.036)|(0.035)|
|Market Research|0.049|0.050|0.046|0.057|0.084|0.104|
||(0.080)|(0.071)|(0.071)|(0.074)|(0.069)|(0.071)|
|Global Collaboration|-0.012|-0.028|-0.020|-0.061|-0.030|-0.057|
||(0.041)|(0.049)|(0.044)|(0.038)|(0.047)|(0.044)|
|GDP Per Capita|4.440+++|4.047++|4.361+++|4.661+++|5.094+++|4.187+++|
|(weighted average)|(1.333)|(1.570)|(1.334)|(1.243)|(1.511)|(1.335)|
|R-sq|0.993|0.993|0.993|0.994|0.993|0.993|

_Specifications have 23 observations and include an unreported constant term. Standard errors in parentheses. + p<0.1, ++ p<.05, +++ p<.01_ In Table 4 we disaggregate spending on knowledge capital by type for the only expenditure type for which we have disaggregated data, reputation and branding. We include only one of the two subcomponents, market research, as expenditures on market research and joint marketing support are highly correlated. Again, the coefficient for R&D is relatively stable across lag periods, suggesting that a 10 percent increase in R&D expenditures is correlated with a 1.2 percent increase in export values and a 1.11.3 percent increase in volumes.

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# **IV.2 FIRM-LEVEL ANALYSIS**

Firms with higher investments in knowledge capital may have higher export and domestic sales, controlling for investments in physical capital. We investigate the association between firm-level exports (and also domestic sales) and spending on knowledge capital by multivariate OLS regression, taking advantage of the constructed panel nature of the data using producer fixed effects. All variables are in natural logs. We vary specification choices over the output measure (values of exports and domestic sales) and the extent of disaggregation of our knowledge capital variables.<sup>21</sup> The results of these estimations are in Table 5.

In columns 1 and 2, we estimate the association of knowledge capital with export and domestic sales, aggregated according to seven types of intangibles spending, namely software, R&D, design, reputation & branding, training, business process improvements, and global collaboration. None of the seven types has a statistically significant relationship with either export or domestic sales.

In columns 3 and 4, we estimate a second (and preferred) specification in which we disaggregate spending on knowledge capital types according to available and conceptually distinct components. In particular, reputation & branding is disaggregated into spending on branding (brand creation and protection, including quality certification, brand naming, trademark registration and license fees per country), spending on local advertising (including ad outlays in local newspapers and specialized magazines, radio/TV and Internet/social networking), and spending on international wine fairs (including participation in international wine shows in the US, UK, China, Germany, Japan, Russia and Brazil). And spending on learning through global collaboration is disaggregated into outlays on foreign consultant services (with global expertise coming in-country) and technology capture trips (structured study tours with local entrepreneurs going abroad). With this additional variation in the data, spending on international wine fairs and on foreign consultant services are both statistically significantly positively correlated with export sales (with the former at the 1% level), while spending on local advertising is statistically significantly positively correlated with domestic sales. Interestingly, spending on international wine fairs has a negative correlation with domestic sales, though this is only at the 10% level of significance; in principle, enterprises that spend more on global brand promotion could be doing so in response to a product mix shift from local to foreign sales. Alternatively, the spending on global brand promotion itself could be resulting in an increase in export demand over time with a diversion in production from domestic to export sales. One additional statistically significant variable is spending on design, which is positively associated with local sales while negatively associated with exports (though only at the 10% level of significance). This could reflect design expenditures (outlays on label, bottle shape design and other elements that provide a distinct image beyond the "name brand") being more sensitive to local than global tastes. Finally, it is interesting that the sizeable spending by firms on branding does not have a statistically significant association with either export or domestic sales in these data. However, this could reflect the much longer asset life of brands; with an average asset life of ten

> 21 We dummy out missing observations for the few cases in which enterprise respondents did not supply a response.

23
years, it is conceivable that spending in prior years would be influencing 2009-2011 sales, and that current spending would be contributing to asset values and sales over the subsequent years.<sup>22</sup>

**Table 5: Association of knowledge capital with firm-level export/ domestic sales**

|_Sales(natural log in 2012 USD):_|(1)<br>Export|(2)<br>Domestic|(3)<br>Export|(4)<br>Domestic|
|---|---|---|---|---|
|Physical Capital Investment|-0.005|0.097|0.057|0.101|
||(0.137)|(0.211)|(0.121)|(0.193)|
|Software|0.017|-0.066|-0.010|-0.073|
||(0.040)|(0.062)|(0.038)|(0.061)|
|R&D|-0.020|-0.002|-0.056|-0.200|
||(0.264)|(0.407)|(0.233)|(0.372)|
|Business Process Improvement|-0.023|-0.054|0.021|-0.024|
||(0.153)|(0.236)|(0.136)|(0.217)|
|Design|-0.084|0.206|-0.213+|0.599+++|
||(0.105)|(0.162)|(0.120)|(0.192)|
|Training|-0.000|0.078|0.021|0.075|
||(0.077)|(0.119)|(0.067)|(0.106)|
|Reputation and Branding|0.038<br>(0.046)|-0.008<br>(0.071)|||
|Branding|||-0.029|-0.020|
||||(0.051)|(0.081)|
|Local Advertising|||-0.180<br>(0.354)|1.734+++<br>(0.566)|
|International Wine Fairs|||0.464+++|-0.329+|
||||(0.121)|(0.193)|
|Global Collaboration|0.124<br>(0.079)|-0.062<br>(0.122)|||
|Foreign Consultant Services|||0.199++<br>(0.086)|0.042<br>(0.138)|
|Technology Capture Trips|||0.016<br>(0.094)|-0.179<br>(0.150)|
|R-squared|0.077|0.069|0.377|0.325|

_Specifications have 72 observations and include an unreported constant term. Standard errors in parentheses. + p<0.1, ++ p<.05, +++ p<.01_ 22 In an unreported alternative specification, we disaggregate total spending on training into outlays on management versus worker upgrading. While neither of these expenditures is statistically significantly associated with either export or domestic sales, all the other statistically significant results are preserved in this specification.

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A key conclusion of the enterprise-level analysis is the importance of carefully disaggregating intangible asset expenditures into specific components that are likely to have an association either with export or domestic sales. An exploration of correlates at too high a level of aggregation may mask statistically significant associations in the underlying constituent variables.

# **V. CONCLUSIONS**

This study has examined the extent to which firms in a developing country invest in particular types of knowledge capital, and the association between these investments and key outcome variables. The study has assembled novel data at the industry and firm levels to test two hypotheses: (i) that spending on knowledge capital is a statistically significant and economically important correlate of growth as reflected in exports, both at industry and firm levels; and (ii) that spending on reputation & branding and on learning through global collaboration that connects firms to better existing knowledge are both statistically significant and economically more important at the firm level than other types of knowledge capital. Our findings support these hypotheses.

The paper began by documenting the extent of within-firm structural change in the Chilean wine industry as reflected in the evolution of export volumes and values over time. We also documented the extent of public and private investments in innovation capabilities through seven key types of knowledge assets, namely software, R&D, design, reputation & branding (outlays on market research, branding, local advertising and international wine fairs; joint marketing support), training (outlays on worker and manager skills upgrading), business process improvement, and learning through global collaboration (primarily outlays on foreign consultant services and technology capture trips). We found that the extent of public sector funding of knowledge capital in the Chilean wine industry over the period 1990-2012 was large, sustained, multi-faceted, and growing over time. Based on firm-level responses, we found that the average life lengths across all assets types are comfortably greater than one year, strongly supporting the case for capitalizing these intangible assets. We also documented linkages between investments in knowledge capital and enterprise risk management. We provided evidence that there may be an important association between investments in knowledge, protection/enabling, insurance and coping/leveraging assets in the Chilean wine industry and the decrease in the monthly volatility of export volumes (and values) over the 1990-2012 period.

We explored empirically the association between investments in different types of knowledge capital and export growth at both industry and firm levels. At the industry level, our findings suggest that a 10 percent increase in R&D spending is correlated with a 1.2 percent increase in export values and a similar increase in volumes, with a significant role played by a demand side control variable (GDP per capita of major export destinations). At the firm level, we find that expenditures on international wine fairs (a component of reputation & branding) and foreign consultant services (a component of global collaboration outlays) are both statistically significantly positively correlated with export sales.

The study raises a number of issues for further study. It suggests that more carefully measuring intangible investments across a more detailed breakdown of types of assets and across more firms would be beneficial. In particular, the large magnitude and statistical significance of R&D investments at the 25
industry level (mainly public but also private outlays) relative to the small magnitude and lack of statistical significance at the firm level suggest that a more disaggregated and more carefully posed set of questions on research expenditures and particularly on development outlays (the “D” side of R&D) may be required to better capture different types of R&D expenditures at the firm level. Finally, aggregated outlays across different sub-types of investments in reputation & branding and global collaboration are not statistically significant. But more disaggregated outlays allow the relative impact on domestic versus export sales to be disentangled—suggesting the importance of collecting data on more narrowly-defined intangible variables in better understanding the various drivers of within-firm productivity.

The methodologies developed to measure and analyze public and private investments in knowledge capital at the industry and firm levels are more broadly applicable. First, a modified version of the firmlevel questionnaire developed and tested as part of this study should in principle be relevant for a better understanding of the within-firm knowledge-related productivity drivers of other agriculture, manufacturing and service industries. This may be particularly insightful for commodity-based industries—such as agro-food processing industries including key agricultural crops, meat and milk products as well as forestry and mining processing industries—where there may not be a sufficient appreciation of the value for business competitiveness of investing in knowledge assets. It is hoped that this study may provide inspiration for future work seeking to better understand the association between knowledge capital and industry- and firm-level productivity. Second, the public-private dimension of the paper raises questions about the appropriability of the publicly-generated benefits by individual firms. There is little doubt that a public program to increase the visibility of Chilean wines in world markets, if successful, would help the representative private firm, but by how much and in what form? Would a positive impact of such investment be captured in the return to existing categories of knowledge capital or would this be more appropriately measured through a new additional category of knowledge capital? Should investments in public asset stocks for the industry be measured separately from the private stocks, and if so, how do they overlap with the private stocks? These are questions to be addressed in further work. Finally, it is hoped that this study may assist in the design of more effective policies to stimulate productivity in a way that helps build shared prosperity for the bottom 40 percent of each country’s population – by spurring further studies to better understand the linkages between support policies and investments in particular types of knowledge capital that help generate more and better jobs over time for the less well-off people in each country.

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