The relative paucity of empirical studies

The efficiency of incentives to promote outward FDI: evidence from Italy

Abstract: The relative paucity of empirical studies of the impacts of outward FDI-specific policies is surprising in light of the strong policy interest in the issue and the active role towards outward FDI that government policy in most countries has taken. Almost no evidence has been so far provided on public incentives to firms' internationalisation. The present paper aims at filling this gap, by providing an empirical analysis on their effects on the firm's growth. Specifically, the analysis applies a methodology which addresses the effects of selection bias and incorporates appropriate counterfactual scenarios. The econometric results, stemming from a two step treatment effect model, reveal that selection for getting the incentive is not a random event, and that incentives are highly effective especially when targeted towards smaller companies. There is ample scope for further research on measuring and assessing the effectiveness of home country policy measures towards O-FDI.

Key words: public policies, incentives, evaluation, outward FDI.

1. Introduction

The last couple of decades registered an unprecedented increase in outward foreign direct investments. In the past, many governments viewed outward FDI as an undesirable transfer of capital and jobs to other countries but, in the 1990s and 2000s, they started look at it as a way to build globally competitive firms, to accelerate the development of high value activities and productivity, to technological transformation and to better allocation of home resources. That is to say that international opinion has shifted significantly as the perceived benefits of FDI are now seen as far outweighing its drawbacks. Governments should be not only attracting more FDI but also doing more to facilitate growing outflows of FDI.

In the developed and developing countries, a large number of home country measures (HCMs) have been offered by the Governments to encourage outward FDI flows (Lou et al., 2009; Sarmah, 2003; UNCTAD, 2001). The rationale for HCMs is that FDI is good for home country development, and also that there are market and coordination failures that deter investments and increase the costs of investing in an environment that is distant in geographical, cultural and institutional terms. Home country measures are launched to overcome such market and coordination failures, encourage outward direct investment as a way to increase the growth and competitiveness of the firms, and also to reap benefits to the home country as whole.

In the field of outward foreign direct investment (O-FDI hereafter), there has been a large body of work that looks at how firms choose their investment destinations, how they behave in host countries, the impact of the investment in host and home countries, the impact of investment climates in the host economy for attracting and sustaining firms. However, the policy and regulatory stance of the capital-exporting country has been largely neglected and formal policies and home country measures (HCMs hereafter) towards O-FDI are even much less discussed (Brewer, 1993; Globerman and Shapiro, 1999; Sarmah, 2003; Te Velde, 2007; UNCTAD, 2001). The relative paucity of empirical studies of the impacts of these FDI-specific policies is also surprising in light of the strong policy interest in the issue and the active role toward FDI that government policy in most countries has taken (Globerman and Shapiro, 1999).

To study the issue is challenging also from a methodological perspective, as there is an increasingly perceived need for improving and developing adequate methodologies for public policy evaluation (see, for example the Special Issue of the International Review of Applied Economics, 2007).

The present paper aims at filling this gap, by providing an empirical analysis on the efficiency of formal policy measures towards O-FDI[1]. The focus is on financial incentives to O-FDI (one type of HCMs) and its effects on the firm's growth. Specifically, the analysis is conducted on 237 Italian firms that received an incentive in the period 1991-2007 vs. a counterfactual sample of firms that internationalised their activity in the same period without any incentive. Data come from Simest, the Italian development finance institution (, and refer to financial incentives addressed to promote Italian companies' FDI outside the European Union. Then, comparing firms that received the incentive with "similar" firms that never received it (our counterfactual sample), we find that the former do actually perform better.

Therefore, the paper offers both a conceptual and an empirical contribution. On the conceptual side, we discuss the effectiveness of public measures to firms' outward FDI, while on the empirical side, we construct an original longitudinal dataset on incentives granted by Simest to Italian companies. Specifically, this is (one of) the first attempts to develop a rigorous evaluation of a policy for the firms' outward internationalisation exploiting the availability of detailed information on the functioning of the program.

The paper is structured as follows. The second Section reviews the state of the art of the literature on policies towards O-FDI and puts forward the research question that drives the empirical analysis. The third Section presents the methodology, while the fourth one describes the data set, the model and the variables employed. Section four concluded with the econometric findings. Our conclusions are reported in Section five.

2. HCMs and FDI

In the developed and developing countries, a number of policy changes occurred and home country measures (HCMs) have been launched by the Governments to encourage outward FDI flows. In this regard, two intuitive questions may arise. Firstly, how and why can home governments promote O-FDI using home country measures (HCMs)? Secondly, in a globalising market economy, does the home country have much significance, as most investment decisions must be market-determined? Are these set of policies efficient in the sense of promoting FDI and growth of the participating companies, while assuring positive effects over the home country activities of the firms?

2.1. Is support necessary? The role of government intervention

Home country institutions, and particularly their enforcement mechanisms (Dunning and Zhang, 2007) are important drivers of national and international competitiveness of firms. The rationale for HCMs is that O-FDI is good for home country welfare by contributing to the growth and competitiveness of firms, and also because there are market and coordination failures that deter investments and increase the costs of O-FDI by firms. Home country governments' actions must be directed at mitigating O-FDI barriers motivated by two primary kinds of market failures: information or co-ordination failures in the international investment process. The promotion of FDI seeks to overcome uncertainties, to make good any shortfalls in resources and capabilities in a company embarking on the internationalisation process, or seeking to invest in an environment that is distant in geographical, cultural and institutional terms (Duran and Ubeda, 2001). Nonetheless, some of these measures set to promote O-FDI may well be contributing to an increase in other type of market failures, as advanced by Brewer in 1993[2]. As far as outward FDI is concerned, Brewer (1993) organised policy actions[3] in 4 quadrants, based on its effects (increase or decrease) over market imperfections and O-FDI.

The studies from Kline (2003), Sarmah (2003) and UNCTAD (2001) suggest that home country measures can be laws, regulations, policies o programmes. Although no major standardized classification of HCMs exist, based on their nature, six broad categories encompass the major types HCMs that are used to promote or otherwise influence FDI flows.

Information provision and technical assistance through organised offices, seminars and workshops or investment missions help the international investor to answer if its worth to invest in the country. This measure is particularly important for SMEs which, on their own, lack the resources needed to conduct a global search of FDI sites.

Financial support, feasibility studies, project development, financial envelopes, loans and equity participation for investment projects in foreign countries, increase the profitability of the investment and reduce the economic risk related to the foreign unfamiliar context and to the firms 'liability of foreigness' (Zaheer, 1995).

Investment insurance schemes protect investing firms from political and other non-commercial risks related to the investment. It can be an effective support for FDI directed into developing countries that tend to pose grater political risks

Fiscal measures, such as fiscal incentives, tax exemptions, deferrals or credits for taxation of foreign source income, general tax sparing provisions increase the financial viability of the investment and permit investors to receive full benefits of the host country tax reductions.

Investment-related trade measures, as market access regulations influence the relative profitability of FDI by enhancing the host country's attractiveness for export-oriented FDI, like granting of special tariffs, quotas or duty preferences to imports from selected countries.

Support for transfer of technology (e.g. support for international technology partnerships; R&D programs, restrictive conditions on the use of patents..). They maybe aimed at strengthening efficiency and productivity as well as competitiveness of the products/services produced in the host country.

More recently, Te Velde (2007) organised the HCMs on the basis of how they can affect motivations for FDI, to developing countries in particular. He identifies four categories of HCMs.

One group of measures provides support for economic fundamentals and governance structures in host countries required for successful investment projects. (e.g. investment in infrastructure, macroeconomic stability, so called FDI- or investment-related aid, untied), particularly important to promote O-FDI in developing regions.

HCMs may reduce the economic and political risks associated with the investment. Financial support, along with improved information about projects and demonstration effects, may improve profitability of projects and reduce uncertainties for foreign investors, thus reducing economic risks. Political risk insurance helps foreign investors to manage political risks, important in countries that have a history of frequent policy reversals.

HCMs can impact on FDI by reducing the information gap in home countries. The provision of information can have spillover effects since investment by one TNC may send positive signals about the host country so that it is followed by investment by other TNCs.

Finally, there are other policies that affect the viability of investment projects, such as trade preferences, tax, labour and competition policy, which may enhance host country's attractiveness, or, otherwise anchor firms to their home economies (e.g. restrictive labour policies).

2.2. The efficiency of the HCMs

There are two main motivations that make public policy evaluation necessary (Wollman, 2007). First of all it is necessary to report about the exploitation of the incentive and effectiveness of public intervention because information asymmetries take place among subjects involved in the exploitation of public aid. Indeed, the successful government intervention implies that the attended social benefits will exceed the financial and administrative costs, stemming from potential economic distortions. Second, public incentive evaluation permits to understand if they should be modified, preserved, enlarged or removed.

The efficiency of the measures towards FDI must be considered at two levels. First, considering the various motivations and determinants for FDI, one may ask at which point certain government policy at home country level can interfere (or interfered) with the firm decision to engage in FDI. Notwithstanding it is hard to capture the incidence of policy variables and their true effects on FDI outflows (Loree and Guisinger, 1995; Duran and Ubeda, 2001). Second, at which point FDI promoted by specific policy measures contributed to the growth and competitiveness of the firm with positive effects in home country welfare. The return from FDI promotion is a particularly important aspect. Take for example the study from Ishida and Matsushima (2008) that demonstrate that any form of governmental intervention to encourage O-FDI can be beneficial only to a certain point, as excessive O-FDI may result in welfare losses in home countries at the expense of consumers' taxes.

We conducted a broad search of the literature in an attempt to identify studies that addressed efficiency of O-FDI policies along these two aspects.

Table 3 brings together a number of studies that evaluate home country policies' effect on O-FDI.

Our search confirmed that there are very few studies addressing the effectiveness of formal policies towards O-FDI. None of these studies look at how FDI promoted by specific policy measures contributed to the growth and competitiveness of the firms and the consequent effects in home country welfare.

The studies can be broadly organised along two lines. A larger group of studies discusses the effects of broad shifts in formal O-FDI policy. A second group discusses in particular HCMs to promote O-FDI.

Out of the first group of studies, several are empirical, but only two deal with micro data (Pradhan, 2004 and Kumar, 2007). The plus part of the papers test the influence of home country policy variables over O-FDI flows at aggregate or industry level, from emerging and developed economies.

From these empirical findings provided so far, it is not clear whether or not Government may interfere with the firm decision to go abroad. It is more consensual that government may both serve as a constraint and as enabling mechanisms of the internationalisation of its national firms, but several factors mediate the efficiency of the policy.

Aharoni and Ramamurti (2008) review of the drivers of internationalization of firms from Japan, Europe, US and some emerging economies does show that home country economic policies towards trade (increase in competition) and outward investment are important determinants of O-FDI, and probably more than home-country economic-development per se.

Globerman and Shapiro (1999) and Shapiro and Globerman (2003) studied the effect of Canadian formal policies towards FDI (inward and outward). Using time-series FDI data over the period 1950-1995, they found that free trade agreements (NAFTA and FTA) appear to have significantly increased levels of inwards and outward FDI. However, Canada's attempt to screen FDI via Foreign Investment Review Agency (FIRA) had no significant effects on either I-FDI or O-FDI.

In 2003, Saphiro and Bloberman test the effect of policy changes across sectors, namely in manufacturing, financial services, and energy. In the study of 2003 the financial services equations contain three additional policy variables: the Bank Act Revision of 1967 that restricted foreign ownership of banks, with the effect expected to be negative, the 1980 less restrictive Bank Act Revision, and the Canada's ''little bang,'' represented by deregulation of securities markets in Ontario in late 1986. They found evidence that FIRA had an effect on both capital inflows and outflows, but only in the manufacturing sector. The effect of the NEP on capital outflows in energy was unambiguous as the program was associated with outflows of capital from the energy sector. In terms of ODI, they find that only the revisions to the Bank Act of 1980 seem to have an effect, that of inducing an increase in Canadian investment abroad. Such variation across sectors, and the importance of public policy, should not be ignored when analyzing foreign investment flows. Nonetheless, they confirm that FDI in Canada and Canadian direct investment abroad do respond to economic signals, the most important of which are GDP in Canada and abroad, exchange rate variations, and relative wages.

Developing and emerging countries launched as well a variety of measures to promote the internationalisation of their firms (Lou et al., 2009; UNCTAD, 2006) and there have been a number of studies addressing the effect of policy changes in the internationalisation of their firms.

Pradhan (2004) and Kumar (2007) identify how the reforms in the Indian government policy impacted positively on O-FDI. The empirical study by Pradhan (2004) in India confirms that economic liberalization in India has had a distinctive impact on the O-FDI behaviour of Indian enterprises. Ceteris paribus, the O-FDI probability of Indian firms increases by 0.019 in the reform period (1993-94 to 2000-01) as compared with the pre-reform period (1990-91 to 1992-93). Kumar's (2007) study is based on data for 4,271 Indian manufacturing firms for 1988/89 to 2000/01. He finds that the variable capturing the effect of the 1991 liberalization of the Government's policy towards investment on O-FDI is robustly positive across different technology classes and across most of the industries. Liberalization has removed the policy constraints on OFDI in addition to promoting the external orientation of enterprises.

Wee (2007) reviews the main steps given by the Thai government to promote O-FDI since the 1990s[4]. He concludes that further efforts are necessary as limited access to finance, the lack of skilled human resources and other host country characteristics still constitute a barrier for firms' internationalisation.

Chinese O-FDI in particular has received considerable attention. Wang (2002) discusses in an appreciative form how the Chinese government has been a 'visible hand' behind China's O-FDI[5]. This policy aims at gaining market share and also to access to capital, technology and know-how from abroad., with a clear aim of making them able to compete in the world market against giant TNCs from developed countries. Buckley et al. (2007) found that liberalisation of Chinese FDI policy in 1992 increased Chinese O-FDI in the period 1984-2001.

However, a recent investment policy review from the OECD (OECD, 2008) concludes that of the five categories of China's OFDI, the government's intervention and influence have been important for projects with the motivation of seeking natural resources, strategic assets and diversification, but have not been very important for projects with the motivation of seeking markets and efficiency. The former three categories of OFDI may be more influenced by the government's strategic agenda, such as securing energy resources and nurturing national champions with international competitiveness. On the other hand, the latter two categories of OFDI are more likely to be a result of purely commercial calculations based on Chinese enterprises' comparative advantage in the host countries. Hong and Sun (2006) found that Chinese O-FDI has moved from being politically to be commercially motivated, with a decreasing role played by government. This perspective is also shared by He and Lyles (2008) who also defend that China's growing O-FDI in the USA is more economic than politically driven, and therefore should be increasingly understood from a business perspective rather than from a political angle.

Otherwise, the results from Liu et al.'s (2005) study of Chinese OFDI determinants in the period 1979-2002 are of a country with patterns of OFDI largely consistent with the Investment Development Path (IDP) hypothesis. They argue that there is no apparent need to cite China's institutions and unique path to economic reform as having a direct influence on OFDI. China's OFDI seems simply to be consistent with an economy at China's level of economic development. Liu et al. (2005) conclude that for policymakers in transitional or developing countries seeking to promote internationalisation through OFDI, the explanatory power of the augmented IDP hypothesis suggests that policies specifically directed at OFDI may be unnecessary, since OFDI seems to follow economic development automatically.

This fading out of government influence is also found by Aggarwal and Agmon (1990). Their study focuses on the international success of developing countries' firms. It identifies three stages of internationalisation of an economy: import substitution; export promotion and foreign direct investment. While the government may initiate the process and control its initial stages, the role of government diminishes as the country and the corporate sector move successfully through the three stages. They claim that the role of the government diminishes as the country and the corporate sector approaches the natural stage of internationalisation.

The second group of studies is formed by four studies that address HCMs in particular. Only one of these (Duran and Ubeda, 2001) is empirical.

Duran and Ubeda (2001) tests the efficiency of Expotecnia, a programme of fairs showing products in various countries with a view to increasing exports and direct investment launched in the 1980s by the Spanish Institute for Foreign Trade. They tested if the firms' probability of investing abroad changed after participating in Expotecnia. Companies participating in these Expotecnia missions receive generic and specific information about the country and suitable arrangement are made for making contacts with local businessman. The study is based on 127 replies to a specific questionnaire, and the variable used for measuring the company's intention to invest is a dichotomous one that takes the value 1 when the company wishes to invest and 0 if it does not. They concluded that the efficiency of the Expotecnia mission in affecting the propensity to invest depends on the degree of internationalisation of the company: is low for companies having only exporting experience; medium for companies that have sales subsidiaries abroad; and high for companies with production facilities abroad.

Te Velde (2007), UNCTAD (2001) and Sarmah (2003) discuss in an appreciative form developed countries measures to promote O-FDI in developing countries. The focus on the UNCTAD (2001) report is on the impact HCMs exert on FDI flows and on how HCMs might increase such flows, including associated technology transfer, to developing countries.

Sarmah (2003) reviews the main HCMs launched by developed countries. He suggests that FDI is attracted to industrial countries due to their opportunity for high returns. Hence, HCMs could play a role mainly in directing O-FDI into developing countries that are usually capital-scarce.

Te Velde (2007) reviews and evaluates the efficiency of United Kingdom HCMs on its FDI in developing countries in the last three decades and discusses under what micro level circumstances are United Kingdom HCMs more effective (e.g. in what industries, or type of country; type of HCMs..). Based on anedoctal evidence Te velde (2007) concludes that investment-related aid has been useful, but political insurance risk insurance provided by the public sector does not seem to have led to additional FDI.(....)

Svetlicic and colleagues address the HCMs that can taken by emerging economies to promote the internationalisation of their firms. The effect of the transformation in the Slovenian policy towards O-FDI is reviewed in detail by Svetlicic (2007)[6]. Svetlicic et al. (2007) indicates main policy actions that home governments should engage to promote SMEs' O-FDI.

2.3. Conditions for efficiency and our research question

It is important to consider the conditions under which HCMs are more likely to be effective, not just whether HCMs affect the O-FDI or not. At the micro level the picture is more anedoctal and mixed. Te Velde (2007 suggests that the effectiveness of HCMs is likely to depend on a number of factors.

A key lesson emerging from the different studies is the importance of enterprises' own technological capacity and size. This gives them the confidence to move beyond and succeed the confines of the domestic market. HCMs in itself may not be able to boost outward FDI if the domestic investors lack the capability to invest abroad.

A number of studies have found that firm size is an important determinant of overseas operations for developed as well as developing country enterprises. Larger firms are more likely to venture abroad than smaller firms, because they often have better access to market information and possess financial strength, allowing them to bear greater risks. Large firms rely less in information and technical assistance provided by public bodies, because they have their own information gathering systems.

Degree of internationalisation of the company seems also to have a positive effect on the probability of OFDI being undertaken (Duran and Ubeda, 2001). International activity enhances the international competitiveness of the enterprise and may also provide valuable information on emerging opportunities in other countries.

The studies reviewed also agree, without empirically testing, that along with firm structural characteristics, the effectiveness of HCMs may also depend on industry, motive for investment, home and host country economic conditions. Some industries are more likely to be users of certain types of HCMs, and the relative importance of each HCMs will vary by industry. Export-intensive, efficiency-seeking investment requires market access, so preferential market access would be a relevant HCM. As referred above, for the case of China, for example, the report from the OECD (2008) concludes that of the five categories of China's OFDI, the government's intervention and influence have been important for projects with the motivation of seeking natural resources, strategic assets and diversification, but have not been very important for projects with the motivation of seeking markets and efficiency. Regarding the destinations countries, Sarmah (2003) suggests that FDI is attracted to industrial countries due to their opportunity for high returns. HCMs could play a role mainly in directing O-FDI into developing countries that are usually capital-scarce.

Hence, these conditions -firm structural characteristics and its international experience, industry, motives for investment and destination country should be taken into account when examining the effects of HCMs.

As we have seen indeed there is only one empirical study testing the effectiveness of specific home country measures. As we have shown, tax and financial incentives for investment abroad constitute a relatively unexplored area also. In this paper we evaluate the efficiency of policy actions in Italy, a country where a number of public instruments aimed at promoting outward FDI (directly or indirectly) are in place (Table 4). Specifically, in this paper we aim at testing the direct impact of public incentives upon the firms' growth (i.e. we focus on the ex post stage). The impact of incentives to firm's international growth may be associated to both direct and indirect effects. The former relate to the explicit/declared intent of the government, while the latter refer to the possible spillovers generated by the firm's internationalisation on the other firms and their local context. Previous empirical works find mixed evidence on the impact of public financial support upon firms' growth (see for example Lerner, 1999, Wallsten, 2000; Merito et al., 2007).

Although we agree on the largely acknowledged issue that outward incentives normally play a less crucial role in determining FDI than the fundamental determinants do (for a survey, see Barba Navaretti and Venables, 2004), our hypothesis is that incentives generally benefit granted firms. Indeed, incentives help internationalising firms to overcome their financial constraints and to gather the needed information to reduce uncertainty and risks related to foreign markets. Moreover policy variables may well be more important than non-policy ones due to the ease with which home governments can quickly alter them (Loree and Guisinguer, 1995). In opposition, non policy determinants, such as market-size and infrastructure, my take many years to modify.NOT SURE HERE OR IN THE CONCLUSION (END)

3. The methodology

The fundamental need for all public policy evaluation is to observe the counterfactual conditions, in order to answer the causal question as to whether the observed outcomes are effectively caused by the public policy and not by other determinants (Marschak, 1953). Because it is impossible to determine exactly what would happen in absence of incentive, as a firm cannot be observed among participants and non participants at the same time, we need a methodology that allows us to compute an average effect of incentive comparing data on participants and non-participant firms, and to identify the causal relationship between the incentive and the outcome, controlling for other possible determinants of the outcome itself (Bartik and Bingham, 1997). Additionally, one has to account for the possible selection bias (Heckman, 1979). Besides the effect of the incentive there may be systematic differences between benefiting firms and not benefiting firms that may affect the impact of the incentive. A selection bias may occur as a result of two different causes: firm self-selection and agency selection. In the first case, firms that apply for the incentive may not be representative of the total population of eligible firms, whilst in the second one, the agency accepts only the applications that meet selection criteria.

Hence, to overcome threats of validity, omitted variables and selection bias, it is necessary to imputate an appropriate counterfactual outcome for the sample of benefiting firms (Moffit, 1991). A variety of different approaches that do not require experimental data have been proposed, but the most utilised are: matching methods, difference in difference and selection models (for a review of non experimental method see Blundell and Costa Dias, 2000). All methods compare a group of benefiting firms, often called treatment group, with a group of not benefiting firms, called control group.

In the present study we use the treatment effect model that is a two-stage selection model where the first step aims to account for the selection and self selection bias, while the second step evaluate the impact of the incentive on the outcome. Namely, two regressions are estimated simultaneously (Lee, 2005): the first one is a probit regression predicting the probability of receiving the incentive; the second one is a linear regression for the outcome (i.e. firm's growth) as a function of the treatment variable (i.e. the incentive), controlling for other observable explanatory variables. Theoretically the solution is to propose and estimate a model of the selection and self-selection decision, that is to define an incentive assignment equation where xi is the set of exogenous covariates that affect the incentive assignment and that could explain different attitudes between benefiting and not benefiting firms. In particular the model assumes that D*i , the probability of receiving the incentive, is a linear function of the observed covariates xi and the random component ei. Specifically we assume that the incentive assignment is determined by:

D*i = xi + ei (Selection equation)

The endogenous binary variable Di is modelled as the outcome of the unobservable latent variable D*i and the observed decision is:

Di = 1, if D*i > 0

Di = 0, if D*i = 0

The second step is made of a linear regression for the outcome yi (i.e. firm's growth) as a function of the treatment variable (i.e. the incentive), controlling for other observable explanatory variables,

yi = dwi + ?Di + ui (Valuation equation),

were wi is the set of exogenous control variables, different from the unobservable latent variable Di, which can influence the response.

4. The empirical analysis

4.1. Data

Simest is the institution dedicated to support and promote Italian companies' international growth outside the European Union. It was set up as a limited company in 1990 and, controlled by the Ministry of International Trade and Commerce, it manages all major public financial instruments supporting outward internationalisation. In this paper we focus on the Law 100/1990, according to which Simest can invest directly in foreign ventures and acquire up to the 25% of the Italian foreign affiliate's equity. The duration of equity shares is in principle up to a maximum of 8 years, within which the pre-agreed reacquisition of Simest shares with partner firms is established. Although Simest can, in principle, evaluate investment proposals from any companies, its priority concerns initiatives by small and medium enterprises (SMEs) to Eastern Europe. Moreover, Simest prefers to acquire interests in foreign firms which are active in the same business sector as the home firm proposing the project; no sector is excluded[7]. This type of HCM may affect firms' decisions to invest abroad to the extent that it reduces economic risk (Te Velde, 2007).

The dataset employed for the empirical analysis combines three different sources of data. Simest's balance sheets provide the information about assignments of incentives to Italian firms, throughout the period 1991-2006. The database Reprint, which provides a census of outward and inward FDI in Italy, since 1986. And, data from AIDA (Bureau van Djick), which provides balance sheet data for Italian firms. Complete information are available for 237 benefiting firms and for 307 not benefiting firms (our control group).

4.2. The model and the variables

Our evaluation model refers to a classical ex-post evaluation (Wollmann, 2007), where the dependent variable has to do with one of the goal attainment, the promotion of SMEs growth[8]. As far as the model, we adopted a traditional treatment effect model (Lee, 2005), which allows us to assess whether the public support affects the growth of benefiting firms vs. not benefiting ones. In particular, as previously illustrated, in order to evaluate the impact of incentive, it is necessary to take into account self selection and selection biases, and then causality. Therefore, our dependent variables are:

  1. D_Incentive is a dummy variable that equals 1 if the firm has received the incentive, and zero otherwise (i.e. first stage, selection equation);
  2. Firm_growth is measured by the rate of growth of the turnover of the Italian parent company between (t0 - 1) and (t0 + 2), where t0 is the year of the foreign initiative (i.e. second stage, evaluation equation).

As far as the first stage, explanatory variables include firm's structural characteristics, firm's financial constraints and project's features related to the country destination and project's size which can affect policy outcome. Therefore, our selection model is:

D_Incentivej = Structural_characteristicsj + Fin_constraintsj + + Project_characteristicsj + ej (Selection equation)

Specifically, as far as explanatory variables are concerned, the proxy employed refer to size and age, which have been traditionally considered as a proxy for managerial skills, thus affecting the firm's ability to obtain external resources (Gonzlez et al., 2005; Blanes and Busom, 2004). Therefore, we expect bigger and older firms to be more likely to obtain the incentive. Previous experience in international markets may also increase the likelihood to both apply and obtain the incentive. Additionally, as the effective cost of going abroad may vary across firms as the result of differences in the availability and cost of financial resources (Desai, 2004 not in the reference list), we proxied the firms' financial constraints by the ratio between their banks debt and turnover. Specifically, as financial markets imperfections can limit the firm's strength of engaging in FDI (Hyytinen and Toivanen, 2005), we expect a positive relationship between variables proxying the existence of firm's financial constraints and the probability of going abroad thanks to the public incentive. As in the process of project selection, Simest evaluates Italian firm's success, we also included a firm's profitability index.

The second stage of the analysis estimates the effect of the incentive on a continuous, fully observed variable which identify the effects (Firm_growthj), conditional on other causes. In section 2 we have discussed that the efficiency from HCMs to promote O-FDI seems to be dependent on several aspects (see also Te Velde, 2007). Therefore, the linear regression function is:

Firm_growthj = D_Incentivej + Structural_characteristicsj + Fin_constraintsj + + Project_characteristicsj + uj (Valuation equation)

Variables considered refer again to firm's structural characteristics, financial constraints and other specific project features, namely the entry mode. Therefore, we included dummies allowing for its nature (greenfield vs. acquisition), the share held by the Italian parent company in the foreign affiliate (majority vs. minority), and the size of the foreign affiliate in terms of employees[9]. Finally, to control for possible differences in opportunities in different areas and sectors, we inserted dummies for the firm localisation by Italian regional area and for the industry of the parent company[10].

The dependent and the explanatory variables are described in Table 5, while Table 6 reports the average values of the variables and the significant differences for the two groups of firms; the correlation matrix is reported in Table 7.

4.3. Econometric findings

The results of the empirical estimates for the treatment model are reported in Table 8. First of all, it is worth observing that, as the correlation between the error terms of the two equations (i.e. the coefficient rho[11]) is significantly different from zero (at p<.01), and so it confirms that both the firm and the project characteristics affect incentive assignment and the latent outcome, therefore in estimating the effects of the incentive a selection bias arises.

As far as the selection model is concerned, results confirm that both the parent company's characteristics and the FDI features explain the likelihood of receiving the incentive. Namely, as already revealed by the descriptive statistics of the two samples (see Table 6), bigger firms with previous international experience are more likely to get the incentive (both Log_Sales and Int_Experience are positive and significant at p<.05 and p<.01, respectively). Likewise, results support also the idea that market imperfections give rise to financial constraints and make firms more likely to apply for (and to get) public funding (BanksD_Sales is positive and significant at p<.05). Interestingly, notwithstanding the selection procedure should a priori favours initiatives to Eastern European countries, the relevant dummy (East_Europe) does not come out significantly different from zero, while the affiliate size does contribute positively to the incentive assignment (Sales_affiliate is significant at p<.01).

As far as the valuation equation, that is our second stage, results confirm the positive and highly significant effect (at p<.01) of the financial incentive on the firms' growth. However, smaller and less indebted companies grow more rapidly (Log_Sales and BanksD_sales are negative and significant at p<.01 and p<.10, respectively) while all the other firm's specificities do not seem to impact on growth. On the contrary, the parent's growth crucially depends on the characteristics of the foreign initiative: indeed, the estimated coefficients confirm that FDI size contributes positively to the firm growth (Empl_affiliate is significant at p<.01), as well as the FDI's localisation in developed countries (North America is positive and significant at p<.05). It may be worth observing that the same results have been obtained from the estimation of an Heckman model (see Table 9), where the second stage is run only on the benefiting firms.

5. Conclusions

Home countries can make use of several measures to promote O-FDI. Simply encouraging O-FDI trough macroeconomic policies may be inefficient. We identified the main categories of them and how they affect FDI. Our survey through the existing literature reveals that not only HCMs are much less discussed than other factors affecting FDI, as also their effectiveness and efficiency have seldom been studied in great detail. There is ample scope for further research on measuring and assessing the effectiveness of home country policy measures towards O-FDI.

So far there has been no systematic discussion or quantification of HCMs in Italy. We analysed a specific Italian HCM, and found positive effects of the financial incentive on the benefiting firm's growth as compared to the counterfactual sample of not benefiting firms. Taking into account the selection and self-selection issue, we can detect the net positive effects of the public incentive. The importance of HCMs for SMEs is mentioned frequently in the central literature of this thematic (e.g. Te Velde, 2007; Svetlicic et al., 2007). Specifically, our results show that financial incentive does help smaller companies to grow also on the home country, thus confirming that the FDI finance gap hinders SMEs in their internationalisation strategy and negatively affects their economic performance. Additionally, the government involvement in FDI may contribute to reduce the uncertainty and risk associated to the unfamiliar host country (Te Velde, 2007), which is obviously more critical for smaller companies that have less financial and management resources to spend for research and analysis prior to embarking into a foreign market (Wright et al., 2007). Our results support Te Velde (2007) Unctad (2001) and Samah (2003) and Svetlicic (2007) postion that the influence of HCMs can be increased through tailor-made approaches and regional and country targeting; on the formulation and administration of measures, as well as the extent to which they complement host country measures and firm level barriers for O-FDI. Last but not the least, the policy effects also depend on the relative cross-national options, in addition to the different motivations for FDI, as stresses by Brewer (1993) and Kokko (2006).

At the best of our knowledge this paper is the first systematic evaluation of public incentives addressing firms' outward internationalisation. However, the agenda for future research is quite rich. The specification of the model presented above should be improved by introducing more adequate measures of certain phenomena. First of all, a better understanding of the selection and self-selection process would benefit from the possibility of accessing data on firms' applications that were not selected for the incentive. Second, firms' internationalisation processes should be modelled taking into account motivations underlying each FDI initiative, although that would require additional data gathering based on surveys and questionnaires. Finally, the effects of public incentives may be also evaluated as far as their indirect impact (associated to externalities and spillovers) is concerned, for example on social welfare. Moreover, our results concern a single type of incentive addressing firms' internationalisation, while a comparative analysis of alternative mechanisms would certainly provide useful suggestions to policy makers for the design of appropriate tools and the improvement of the existing ones.

Policy variables may well be more important than non-policy ones due to the ease with which home governments can quickly alter them (Loree and Guisinguer, 1995). In opposition, non policy determinants, such as market-size and infrastructure, my take many years to modify. Nonetheless, the findings of this paper seem to justify greater research efforts in the directions indicated.


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  1. As Globerman and Shapiro, we refer to formal foreign investment policies, in order to distinguish them from other policies that might affect FDI, but which are directed primarily at other targets. For example, labour policies. In this regard note that Dewit, Grg and Montagna (2009) study of O-FDI from OECD countries shows that high level of domestic employment rigidities and regulations discourage O-FDI, making firms 'anchored' to their locations. Competition policy is another field expected to have an effect over O-FDI. Public policies directed at inward FDI may also directly or indirectly affect outward flows (ODI). In general, policies reducing the profitability of local investments might encourage increased O-FDI.
  2. In what can be considered a seminal article on the effects of home country public policies over inward and outward FDI, Brewer (1993) delineates a set of home country policies and their effects on market imperfections and FDI. Home country financial measures associated with outbound FDI can also affect the composition of the bundle of factors that are transferred internationally for an FDI project, may affect the initial investment but not reinvested earnings, and so on. These aspects are not considered in our paper.
  3. Some of the measures considered are not specific polcieis towards FDI but they affect nevertheless indirectly FDI flows.
  4. Including bilateral investment treaties and double taxationconventions, institutional support to firms' interationalisation projects.
  5. The government acted as information provider, encouraged domestic enterprises to specific sectors, and granted special finance and tax incentives to domestic firms' international investment in strategic industries.
  6. The new policy included not only financial support (e.g for start-up costs) as also programs designed to support firms' internationalisation projects through training and studies and the development of the foreign offices representation, the establishment of conventions to eliminate double taxation with over 35 countries, as well as investment treaties with over 47 countries.
  7. From the beginning of the activity up to the end of 2006, Simest acquired shareholdings in 469 Italian foreign affiliates, subscribed 150 capital increases for a total of 412 millions of euro and sold 253 shareholdings for a total of 193.4 millions of euro.
  8. This is also in line with most of the empirical literature that recognizes growth at the firm level as a good proxy for the effects of industrial policy measures (e.g. Fisher and Reuber, 2003).
  9. We also tried sales of the foreign affiliate. However, as it is highly correlated with employment (the correlation being 0.859), we decided to keep only the former, as it comes out more significant in the econometric estimates.
  10. Ten industry dummies have been considered: services, wood products, raw materials, chemical and pharmaceutical, building and construction, electronics, industrial machinery, automotive, food tobacco and beverages, textile, with plastic and rubber as baseline.
  11. STATA provides an estimate of rho (the correlation between the error terms of the two equations), sigma (s, the standard error of the outcome regression if linear) and lambda (l = r*s). Namely, STATA automatically tests whether r=0 (or equivalently, whether l=0, since s>0).

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