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The economic and institutional determinants in the international delocalisation of Italian companies

The economic and institutional determinants in the international delocalisation of Italian companies Int. J. Trade and Global Markets, Vol. 15, No. 2, 2022 135 The economic and institutional determinants in the international delocalisation of Italian companies Klodian Muço Catholic University “Our Lady of Good Council”, Research Centre on Economics of Transition Countries, 1000 Tiranë, Albania Email: k.muco@unizkm.al Ela Golemi* Economics Department, Aleksandër University of Durrës, 2001 Durrës, Albania Email: golemiela31@yahoo.com *Corresponding author Abstract: The latest trend of companies is that of fragmenting their production across several countries as a cost-saving policy. The selection of an optimal location for the fragmentation of the production depends on the economic, fiscal and institutional factors. This paper examines the main factors that influence the process of delocalisation of Italian companies in the Balkans. The results suggest that the work cost and productivity of the hosting country encourage the Italian enterprises to fragment their production in the given country. The empirical results of this study also suggest that institutional factors such as rule of law and corruption have a positive and significant correlation in the delocalisation. Finally, this study empirically examines the impact of fiscal factors. The results suggest that Italian companies are not influenced by the fiscal pressure of the host country. Keywords: international delocalisation of production; Italian companies; cost of production; delocalisation; productivity; corruption; rule of law. Reference to this paper should be made as follows: Muço, K. and Golemi, E. (2022) ‘The economic and institutional determinants in the international delocalisation of Italian companies’, Int. J. Trade and Global Markets, Vol. 15, No. 2, pp.135–148. Biographical notes: Klodian Muço is a Lecturer in the Research Centre on Economics of Transition Countries at Catholic University “Our Lady of Good Council”. He holds a BSc degree in Economics from Bergamo University, Italy. Following a MSc degree in Economic Organization and Business Development in International Markets from Bergamo University, Italy and a PhD in Political Economy from Insubria University, Italy. He was a Visiting researcher at Macerata University and at Bocconi University, also was a Post Doc from Fribourg University, Switzerland. Previously, he was Head of the Department in Political Economy and Tourism at the “Eqrem Çabej” University and Lecturer in the Faculty of Fastip at Aleksandër Moisiu University of Durrës. Copyright © The Author(s) 2022. Published by Inderscience Publishers Ltd. This is an Open Access Article distributed under the CC BY license. (http://creativecommons.org/licenses/by/4.0/) 136 K. Muço and E. Golemi Ela Golemi, PhD, is Professor of Macroeconomics and International Economics, member of Economics Department, University “Alexander Moisiu” Durrës. From 2016 to 2020, she has held the position of Dean of the Faculty of Integrated Studies with Practice and Vice Dean for Scientific Research at the Faculty of Business, University of Durrës. Her scientific activity focuses on sustainable economic development, financial stability and the Western Balkans’ economic policies for European Union integration, on which she has authored scientific articles and published them in reputable scientific journals. He has participated actively in many international scientific conferences, symposia and seminars in Europe and the USA. 1 Introduction In the recent years, the economic literature has paid special attention to the international fragmentation of production. Many studies have identified the growth of this phenomenon in question, its characteristics and the factors that lead to delocalisation of production (Ferrucci and Picciotti, 2017; Fratocchi et al., 2016; Cardullo et al., 2013; Popescu, 2013; Crestanello and Tattara, 2011; Pickles and Smith, 2011; Amighini et al., 2010). According to a study published in 2017, it turns out that three to five million manufacturing jobs have been lost because of offshoring. The report published by the European Restructuring Monitor (2016, p.31) affirms that during the period 2003–2016, 44.74% of jobs in the manufacturing sector of the European Union were lost by offshoring. The fragmentation process according to the report in question is focused on developed EU countries that also have high wages. According to Graziani (2001) and Yeaple (2003) the process in question is developed mainly for labour-intensive industries, which by fragmenting production to nearby countries with low input prices, can reduce unit costs of final products. Based on the above facts, the objective of this study is the analysis of factors that influence the selection of a country in the Balkan area by Italian companies at the moment when they decide to delocalise production process. Our analysis takes into account two groups of factors, economic and institutional. Our basic hypothesis is that: when Italian companies decide to delocalise they choose not only depending on the lower cost of labour input, but above all they take into account institutional factors such as rule of law and corruption. To confirm this hypothesis in this paper through a data panel, two empirical models will be made to see the impact of economic factors such as: labour cost, productivity and total tax rate, including institutional factors such as: rule of law, political stability and corruption, in the process of delocalisation of the Italian companies in one of the nine Balkan countries – Albania, Bosnia, Serbia, Macedonia, Montenegro, Bulgaria, Croatia, Rumania and Slovenia. The main results of this study show that Italian companies when they decide to delocalise production in one of the countries of the Balkan area, are not only influenced by labour costs, as affirmed by the vast majority of literature (Crestanello and Tattara, 2011; Amighini et al., 2010; Cietta, 2008; De Nardis and Traù, 2005; Helg and Tajoli, 2005), but they are also influenced by institutional factors such as the rule of law and corruption. Therefore, they prefer to evaluate direct and indirect costs in the complex. The economic and institutional determinants 137 The rest of the study is organised as follows: the next section presents the review of the empirical literature review and discusses the empirical model and cost estimation issues, while the results from the empirical analysis follow in Section 4, and finally Section 5 is a final conclusion of the above. 2 Theoretical predictions and literature review Over the last three decades, the progressive liberalisation of transactions, the progress in production technology, the reduction of transport costs and the logistical progress have all given opportunities and incentives to many different enterprises for the process of fragmentation of production and its geographical delocalisation. Today more and more we see that different companies produce intermediate products in different countries, or more precisely they fragment production. R&D, design, package, marketing, distribution, etc having as a primary objective the reduction of production costs and growth of comparative advantage (Nicita et al., 2013). This distribution of production processes depends on the geographical position and the nature of a product (UNCTAD, 2010), on the distribution of the power of the leading manufacturing firm (Gereffi, 1999; Altenburg, 2000) and the role of government institutions and incentive policies for foreign investment in a country (Sturgeon and Gereffi, 2012; Muço et al., 2018). According to traditional theory, there are two types of foreign direct investment (FDI) horizontal and vertical. Horizontal FDIs occur when firms produce similar goods and services in different countries to overcome transport barriers and reach the final consumer (Markusen, 2002). These types of investments are not the subject of our study. While vertical FDIs, have to do with the fragmentation of the production process in stages, to take advantage of differences in the price of inputs (Bronzini, 2010). This process is also known as offshoring. According to the study by Feinberg and Keane (2006) 19% of American multinationals have performed vertical FDIs in Canada to reduce production costs. This type of process according to Yeaple (2003) is highly developed since the companies operating in developed countries can reduce the unit cost of final products by shifting production to nearby countries that have low input prices. Various empirical studies have shown that in terms of production costs, labour cost is the primary factor that explains the international fragmentation of production (Crestanello and Tattara, 2011; Cietta, 2008; De Nardis and Traù, 2005; Helg and Tajoli, 2005). Reducing labour costs according to Giusti (2006) is an important factor that leads to increased competition in different countries, this often leads Italian companies to think that the delocalisation of production would make them more competitive in the market. This best motivates the fact that Italian companies which have delocalised production are mostly labour-intensive manufacturing companies operating in the textile and metal industry (Amighini et al., 2010). Most of these Italian companies started the delocalisation process in the early 1990s immediately after the German ones (Graziani, 2001). It is worth mentioning the fact that according to some statistics published by the Bureau of Labour in the USA (Bureau of Labor Statistics, 2012) it is noted that in China and India in 2003 the cost per hour was respectively 0.62 dollars and 0.81 dollars while in Italy, the target country of our study, it was 23.35 dollars. 138 K. Muço and E. Golemi It is worth noting that labour cost is only one of the factors that stimulates the delocalisation of production in a given country, as there are other factors such as: productivity (Pickles and Smith, 2011), distance, flexibility at work (Amighini et al., 2010; Rodrik, 1997), union pressure (Cardullo et al., 2013), similarities with the local system and culture (Powell and Di Maggio, 1983), linguistic knowledge of the host country, if they know the language spoken by the investor (Muço et al., 2018), political and institutional stability of the host country (Helpman, 1984), the level of corruption in the host country (Muço and Balliu, 2018), European Union membership, as member county companies want to relocate production other EU member states (Pickles and Smith, 2011). In addition, we need to highlight the differences in fiscal pressure between the developed countries and the countries that they choose to fragment production (Rabushka, 2003; Mitchell, 2004) as well as the fiscal incentives provided by FDIs host countries from developed countries (Muço et al., 2018). Production is also often delocalised due to the influence of new markets, for example, many Italian companies have delocalised production in China as it is the second largest retail market in the world and consequently sales of luxury products made in Italy are highly demanded (Ferrucci and Picciotti, 2017; Chevalier and Lu, 2009). According to institutional theories (Powell and Di Maggio, 1983), companies are driven by positive judgments of stakeholders who assess the appropriateness of strategic activities in order to develop their business activity. In other words, they are the ones who decide where the production should be moved and they are the ones who choose depending on the economic interests, the institutional environment of the host country and the fiscal pressure. According to North (1991) such enterprises tend to interact with other local firms but not only in order to improve their ability, to survive and thrive. Other factors that stimulate the delocalisation of production are the host countries which, knowing that FDIs transfers technology, offer them a number of advantages and have an impact on productivity growth (Amiti and Wei, 2006; Olsen, 2006). They tend to improve governance and regulate markets (Gereffi and Mayer, 2004), to reform the banking system, to reduce bureaucracy, to guarantee the free market (Demirbag et al., 2007) and to improve public administration (Batley and Larbi, 2004). Another factor is also the presence of other companies of the same nationality but not only. According to Popescu (2013), Italian shoe and textile manufacturers go to Timisoara because there is an important cluster and in this cluster there is a large presence of Italian companies. It should also be affirmed that during the last years there has been not only delocalisation of enterprises but also their return to the country of origin, i.e., reshoring (Ferrucci and Picciotti, 2017). This is done after a reassessment of the company to rebuild the production capacity in the country (Fratocchi et al., 2016) and also thanks to the intervention of the government. Aiming to cope with the economic crisis, the governments apply the perspective of re-industrialisation (Pisano and Shih, 2012). It is also important to mention the image of the production of a product in a developed country in contrast to the production in a third world country. This is especially true for luxury products in the textile sector. Returning to the origin country (reshoring) has also a positive impact on the increase of employment rate as delocalisation itself leads to unemployment (Crinò, 2009; Becker and Muendler, 2008; Corò and Volpe, 2006). However, the issue of unemployment or job loss due to delocalisation is not always supported in various studies (Falzoni and Tajoli, 2008; Amiti and Wei, 2004; Viesti and Prota, 2007). The economic and institutional determinants 139 3 Data and methodology The data used in this study are micro data, which make it possible to assess the impact of economic, fiscal and institutional factors on the delocalisation of Italian enterprises in one of the Balkan countries. To conduct this study we have created a data panel with data published by the Italian National Institute for Foreign Trade (ICE). The time series taken in this study include the period 2010–2018. To avoid data heterogeneity, we have not included other sources of information from different business associations for the delocalisation of Italian enterprises. Using them could help us expand the database and increase the number of observations but on the other hand we could have data inconsistencies. In this study we have included nine Balkan countries – Albania, Bulgaria, Bosnia, Croatia, Macedonia, Montenegro, Romania, Serbia, Slovenia. We have excluded Kosovo, Turkey and Greece from this study, due to lack of data and/or because they have a completely different economic structure compared to that of other countries included in the panel. The objective of this paper is the empirical verification of the impact that economic, fiscal and institutional factors have on the delocalisation of Italian enterprises in the Balkans. More specifically we will assess the impact that labour costs have on the delocalisation of production where according to many studies is one of the main factors that explains the international fragmentation of production (Crestanello and Tattara, 2011; Amighini et al., 2010; Cietta, 2008; De Nardis and Traù, 2005; Helg and Tajoli, 2005) and stimulates competition (Giusti, 2006). We want to verify the impact that there is a difference in fiscal pressure between the country of origin and the destination, in the delocalisation of production, where according to Rabushka (2003) and Mitchell (2004) taxes play an important role in attracting foreign investors. Last but not least, we will also empirically assess the impact that institutional factors have on the localisation of Italian investments in a particular Balkan country. In other words, we will assess the impact of corruption, rule of law and political stability of the host country on the withdrawal of Italian companies which according to various studies play an important role (Muço and Balliu, 2018; Helpman, 1984). To carry out this study we have selected as a dependent variable the Italian companies delocalised for every 100,000 inhabitants in the nine Balkan countries. As independent variables we have selected the economic and fiscal factors – Labour Cost, Productivity and Total Tax Rate and the institutional ones – Rule of Law, Political Stability, and Corruption. In order to have a thorough perspective of the study, it would be interesting to have data on the ‘loss’ of jobs in Italy to verify whether or not the results achieved by various studies on the verification of job losses from delocalisation can be verified (Crinò, 2009; Becker and Muendler, 2008; Corò and Volpe, 2006; Falzoni and Tajoli, 2008; Amiti and Wei, 2004; Viesti and Prota, 2007). However, it is impossible to collect reliable data. 140 K. Muço and E. Golemi 4 Empirical results In this section we discuss the empirical results of our study. As mentioned in the previous paragraph, our goal is to empirically highlight the economic, fiscal and institutional factors that influence Italian companies to delocalise to a particular country in the Balkan area. We set out to examine the main costs that should be borne by a company that delocalises production in a given country using indicators, such as, productivity, total tax volume, political stability and corruption. Figure 1 shows the trend of the delocalisation of Italian companies for every 100,000 inhabitants in a given country for the time period 2010–2018. The given graph shows that the country with the highest presence of Italian companies for every 100,000 inhabitants is Slovenia, a EU country. Slovenia is the country with the highest average salary in the Balkan area, about 1800 euros. But if we see data on turnover and employment of Italian companies in this country, Slovenia occupies the last place. Figure 1 Italian firms per 100,000 inhabitants (see online version for colours) Italian companies are more numerous in Romania, with about 53.6% of companies in total (6300) delocalised in the Balkan area (2018). The number of employees in Italian companies in this country reaches about 97,034 workers out of 190,000 workers in total in all the Italian companies located in the Balkan area. The annual turnover of Italian companies in Romania reaches about 7.3 billion euro out of an annual turnover of 14.6 billion in the Balkan area. In Figure 2, Romania seems to have a very positive growing trend for the period 2010–2013, whereas in the last two years the trend is decreasing. The two Balkan countries that attract the most Italian companies in the period in question are Serbia and Albania. In Serbia, the average number of Italian companies that have delocalised production is 460 with over 20 000 employees and about 2.2 billion in annual turnover. In Albania, on the other hand, the number of Italian companies is around The economic and institutional determinants 141 350, the number of employees is about a quarter of that of Serbia (7600) the annual turnover instead is about one fifth of that of Serbia 0.381 billion euro. Figure 2 Performance of some indicators for Western Balkan countries (see online version for colours) The graph shows clearly that Croatia is another EU country preferred by Italian companies. The number of Italian companies that have delocalised part of production to this country is over 460. The number of employees is around 14,000 and annual turnover is over 1.4 billion. By analysing the ICE data it is clear that the cost of labour is not the main factor that stimulates Italian companies to decide to delocalise to a particular country, if this were 142 K. Muço and E. Golemi true then the greatest concentration of Italian companies would be in Albania which is the country with the lowest level of average salary (426 euros). Below we see the other factors that may influence Italian companies to delocalise to one of the Balkan countries. In the first graph we see productivity by country, and there is a similar productivity trend from $27,240 in 2010 to $29,804 in 2018 in Albania; from $60,829 in 2010 to $71,589 in 2018 in Slovenia. Focusing on the value of productivity we see that Italy has the highest level of productivity ($92,296 for 2018) compared to all other Balkan countries where it delocalises production (the average of Balkan country for Output per worker (GDP constant 2011 international $ in PPP) in 2018 was $45,457, respectively ($29,804 in Albania; $39,101 in Bosnia and Herzegovina; $43,214 in Bulgaria; $57,475 in Croatia; $37,894 in North Macedonia; $48,123 in Montenegro $55,124 in Romania; $29,451 in Serbia; $71,589 in Slovenia). What is interesting about this graph is the fact that the EU countries have the highest level of productivity. The productivity of developing countries is obviously lower. Regarding the cost of hourly labour under PPP, it is much lower in Bulgaria ($13.06) and Albania ($4.62) where the average level of salaries is much lower than in all the Balkan countries including Bulgaria. Slovenia and Romania also have a relatively low hourly labour cost according to PPP. In the latter, the cost of hourly labour under PPP (respectively $27.16 and $15.11) has increased substantially in the time period 2011–2012. This period coincides with strong pressure from trade unions to improve working conditions and salary levels in Romania. An interesting fact to note is the case of Albania which despite having a very low salary level, the cost of hourly labour under PPP is similar with that of the Balkan countries. In the third graph we see the percentage of profit taxes. North Macedonia is the country with the lowest percentage level of profit tax until 2014. We need to highlight that according to the World Bank report for 2014 and 2015 the growth of real GDP for North Macedonia was 3.7% which is the highest in the Balkan area. The decrease in profit taxes has influenced the increase in FDIs in North Macedonia, which rose from 0.54% of GDP in 2014 to 2.95% of GDP in 2015 and 5.04% of GDP in 2016, 3.37% of GDP in 2017 and 5.12% of GDP in 2018 (WB, 2018). Croatia is the country with the lowest level of profit tax in the period in question. The last three graphs represent the institutional factors, such as, political stability, perception of corruption and rule of law. All these three indicators have been estimated. The values for these three indicators vary from high to low, that is, the lower the values, the less the perceived corruption, the better the political stability and the rule of law. For the three last graphs we can say that the sooner a country enters the EU, the better its institutional factors are. Albania and North Macedonia are the countries with the highest corruption index and lowest political stability. That is why these are the last two countries from those taken into consideration that have not yet opened the negotiations for accession to the EU, the decision for the opening of the negotiations for these two countries was taken in 24 March 2020. Below we see the empirical results of the impact of labour cost, productivity and total tax rate in percentage of commercial profit on the delocalisation of Italian companies in the Balkan area. The economic and institutional determinants 143 The variables of interest – productivity, labour cost, tax rate are assessed as differences from the Italian level, since it is this difference which should stimulate Italian companies to delocalise. From the Table 1 we see that delta labour cost (DLC) is correlated with Italian firms for 100,000 inhabitants. DLC have a positive and significant effect. The higher the cost of labour in a given country compared to Italy, the lower the number of Italian companies that delocalise production to that country. This result shows what has been said in the literature which we cited in the previous paragraphs, that low labour costs in a certain country encourage Italian companies to delocalise production to that country. The panel with DLC has an R = 0.26 which indicates 26% of the dependent variable is explained by the DLC. Table 1 The ‘economic/fiscal’ factors Dep. variables: Panel Panel Panel Italian firms per 100,000 inhabitants Fixed effects Fixed effects Fixed effects Delta Labour Cost –0.111* (constant 2011 PPP) (0.054) Delta Productivity 0.0002** (constant 2011 PPP) (0.000) Delta Total Tax Rate 0.314 (% of commercial profits) (1.144) Constant (average fixed effect) 7.22*** 16.30*** 8.19*** (0.416) (2.736) (0.369) Country Fixed Effects Yes Yes Yes F(1,8); Prob. > F 4.33; 0.07 9.02; 0.01 0.08; 0.79 R-sq within 0.26 0.13 0.00 R-sq between 0.09 0.13 0.05 R-sq overall 0.08 0.13 0.03 Countries 9 9 9 Years 6 6 6 Observations 54 54 54 Delta: Value Country i – Value Italy. Robust (clustered) standard errors in brackets. Sign: *: 10%; **: ù 5%; ***: 1%. The delta productivity (DP) has a negative but very small significant effect. The higher the productivity of labour in a country compared to Italy, the more Italian companies try to delocalise production to that particular country. In fact, from the descriptive statistics we know that productivity is lower than in Italy. Therefore, “the lower the negative difference compared to Italy is, the more numerous the Italian companies will be in that particular country”. In this model R = 0.13 which indicates 13% of the dependent variable is explained by the DP. The third independent variable that we take into consideration to explain the delocalisation of Italian companies is the Delta Total Tax Rate (% of commercial profits). This variable does not explain the dependent variable. The coefficient is not significant, 144 K. Muço and E. Golemi the R is very low and the F-stat is not significant. The explanation of the lack of significance of the variable in question could be the following: even though Italian companies delocalise production to the countries taken into consideration, still pay taxes in Italy and not in the country to which they have delocalised production. In Table 2 the dependent variable is again “Italian firms per 100,000 inhabitants”. As explanatory variables in this model serve the indicators of worldwide governance to understand the impact that good governance has on attracting Italian companies that want to delocalise production. The indicators we have chosen are: Political Stability (an index that measures the perception of the probability that the government will be destabilised or overturned by unconstitutional or violent means, including political violence and terrorism); Rule of Law (perception of individuals of the respectability of rules in society, which in particular measures the degree of execution of a contract, property rights, performance of the police and the judiciary, and also the probability of the presence of crime and violence); Corruption – an index that measures the perception of the citizens of how corrupt government officials are. Table 2 The ‘institutional’ factors Dep. Var.: Panel Panel Panel Italian firms per 100,000 inhabitants Fixed effects Fixed effects Fixed effects Rule of law 5.51** (2.08) Political stability 1.32 (0.91) Corruption 0.109** (0.011) Constant (average fixed effect) 8.19*** 7.87*** 3.50* (0.041) (0.151) (1.531) Country fixed effects Yes yes yes F(1,8); Prob. > F 7.00; 0.03 2.08; 0.19 8.96; 0.02 R-sq within 0.32 0.19 0.32 R-sq between 0.19 0.38 0.12 R-sq overall 0.19 0.34 0.12 Countries 9 9 9 Years 6 6 6 Observations 54 54 54 Robust (clustered) standard errors in brackets. Sign: *: 10%; **: 5%; ***: 1%. From the results of the second model we see that Rule of Law has a positive and significant impact on the delocalisation of Italian companies to a particular Balkan country. The model has an R = 0.32 which explains that 32% of the dependent variable is explained by the independent variable Rule of Law. The second explanatory variable, political stability has an insignificant correlation with the dependent variable; the F-stat coefficient is insignificant. The economic and institutional determinants 145 The third variable, corruption has a significant and positive correlation with the dependent variable. The R also in this case is equal to 0.32 which explains that 32% of dependent variable is explained by the independent variable, corruption. If we see the model in its entirety, it seems that the impact of the explanatory variables Rule of Law and Corruption is contradictory. No, the truth is that Italian companies seek out countries with credible and effective public institutions, but prefer countries where government officials can be manipulated, i.e., that favour Italian companies through biased processes while at the same time operating within the limits of the law. 5 Conclusions In this paper we study the impact that economic, fiscal and institutional factors have on the delocalisation of Italian companies in one of the Balkan countries. Compared to previous empirical literature, our analysis has the advantage of micro- homogenised data obtained from the Italian Trade Inspector (ICE). In the first model, the empirical analysis conducted in this study showed that labour costs and productivity of the host country encourage Italian enterprises to delocalise production in that country. While in the second model, the empirical analysis showed that institutional factors such as rule of law and corruption have a positive and significant correlation with the delocalisation of Italian companies in the Balkans. In this paper we also examined the fiscal factors, tax rate in % of commercial profits. In this case the results suggested that Italian companies are not influenced by the fiscal pressure of the host country because even when they delocalise parts of production, given that the parent company is in Italy, they still pay taxes in Italy. Therefore, the level of taxation does not influence the choice of a place for delocalisation of production. Both the empirical analysis and the review of the theoretical literature, affirm in a way what the vast majority of the empirical literature says that the cost of labour in the complex is one of the main factors leading to the international fragmentation of production. The results of this study make an important contribution to the empirical economic literature. These results confirm that Italian companies when delocalising production do not take into account the level of taxation of a country. They generally consider the reduction in production costs per unit. And the investment guarantee in that country which depends on institutional factors. The empirical results also show a very interesting fact, that Italian companies that delocalise production are not negatively influenced by the level of corruption of the host country. This in a way means that Italian companies that delocalise production sometimes cope with corruption. As a result they that have a little corruption which sometimes serves to fight bureaucracy. From the descriptive analysis of the data it was noticed that the delocalisation of Italian enterprises has a positive impact on employment growth in the host country although this impact was relatively not very significant in % with the total employment ratio. As in the other empirical studies considered in this study, we were unable to measure the loss of jobs in Italy due to the delocalisation of production in the Balkans. 146 K. Muço and E. Golemi References Altenburg, T. (2000) Linkages and Spill-Overs between Transnational Corporations and Small and Medium-Sized Enterprises in Developing Countries: Opportunities and Policies, Reports and Working Papers 5/2000, Berlin 2000, ISBN 3-88985-217-3. Amighini, A., Presbitero, A. and Richiardi, M. (2010) ‘Delocalizzazione produttiva e mix occupazionale’, Workshop: ‘I cambiamenti della manifattura italiana visti attraverso l’indagine Unicredit’. Amiti, M. and Wei, S.J. 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(2004) ‘The economics of tax competition: harmonization vs. liberalization’, Index of Economic Freedom, Heritage Foundation, Vol. 25, p.38. Muço, K. and Balliu, G. (2018) ‘Crescita economica e corruzione: quale impatto nei paesi balcanici?’, Moneta e Credito, Vol. 71, No. 284, pp.297–309. Muço, K., Valentini, E. and Lucarelli, S. (2018) ‘The impact of foreign direct investment on the productivity of the Balkan countries’, Journal Transition Studies Review, Vol. 25, No. 2, pp.37–54. Nicita, A., Ognivtsev, V. and Shirotori, M. (2013) Global Supply Chains: Trade and Economic Policies for Developing Countries, UN. North, D.C. (1991) ‘Institutions’, Journal of Economic Perspectives, Vol. 5, No. 1, pp.97–112. Olsen, K.B. (2006) Productivity Impacts of Offshoring and Outsourcing: A Review, Working Paper 2006/1, Directorate for Science, Technology and Industry (STI), OECD, Paris and Washington, DC. Pickles, J. and Smith, A. (2011) ‘Delocalization and persistence in the European clothing industry: the reconfiguration of trade and production networks’, Regional Studies, Vol. 45, No. 2, pp.167–185. Pisano, G.P. and Shih, W.C. (2012) ‘Does America really need manufacturing’, Harvard Business Review, Vol. 90, No. 3, pp.94–102. Popescu, C. (2013) ‘From Veneto (Italy) to Timisoara (Romania): the birth of an industrial cluster’, Human Geographies, Vol. 7, No. 2, p.15. Powell, W. and Di Maggio, P. (1983) ‘Institutionalism isomorphism and collective rationality’, American Sociological Review, Vol. 48, pp.147–160. Rabushka, A. (2003) ‘Representation without taxation’, Policy Review, Vol. 122, p.67. Rodrik, D. (1997) Has International Economic Integration Gone Too Far?, Institute for International Economics, Washington, DC, p.128, Copy at https://j.mp/2ow2hqX Sturgeon, T. and Gereffi, G. (2012) ‘Measuring success in the global economy: international trade, industrial upgrading, and business function outsourcing in global value chains’, in Pietrobelli, C. and Rasiah (Eds.): Evidence-Based Development Economics, pp.249–280. UNCTAD (2010) Integrating Developing Countries’ SMEs into Global Value Chains, UNCTAD/DIAE/ED/2009/5, New York and Geneva. 148 K. Muço and E. Golemi Viesti, G. and Prota, F. (2007) ‘Delocalizzazione e Made in Italy: il caso pugliese’, L’Internaziona-lizzazione dei sistemi produttivi del Mezzogiorno. Strumenti per la PA, a cura di A. Rossi e A. Cenderello, Quaderni Formez, p.61. Yeaple, S.R. (2003) ‘The complex integration strategies of multinationals and cross country dependencies in the structure of foreign direct investment’, Journal of International Economics, Vol. 60, pp.293–314. Notes The data is collected from ICE, 2018. ICE takes into account only companies whichhave delocalised parts of production abroad and have a certain number of employees and annual turnover over 1 million. World Bank, South East Europe Regular Economic Report, No. 9, 2016, p.18. Bibliography Adekola, A. and Sergi, B.S. (2016) Global Business Management: A Cross-Cultural Perspective, Routledge, New York. Eurofound (2016) ERM Annual Report 2016: Globalization Slowdown? Recent Evidence of Offshoring and Reshoring in Europe, Publications Office of the European Union, Luxembourg. Galgoczi, B. and Sergi, B.S. (2012) ‘Social and economic trends in South-East Europe’, South-East Europe Review for Labour and Social Affairs in Eastern Europe, Vol. 15, No. 1, pp.51–60. Sergi, B.S. (2003) Economic Dynamics in Transitional Economies: The Four-P Governments, the EU Enlargement, and the Bruxelles Consensus, Routledge, New York. Sergi, B.S. and Qerimi, Q. (2008) The Political Economy of Southeast Europe from 1990 to the Present: Challenges and Opportunities, Continuum, New York. Sergi, B.S. and Scanlon, C.C. (2019) Entrepreneurship and Development in the 21st Century, Emerald Publishing Limited, pp.241–248, https://doi.org/10.1108/978-1-78973-233- http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Trade and Global Markets Inderscience Publishers

The economic and institutional determinants in the international delocalisation of Italian companies

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Int. J. Trade and Global Markets, Vol. 15, No. 2, 2022 135 The economic and institutional determinants in the international delocalisation of Italian companies Klodian Muço Catholic University “Our Lady of Good Council”, Research Centre on Economics of Transition Countries, 1000 Tiranë, Albania Email: k.muco@unizkm.al Ela Golemi* Economics Department, Aleksandër University of Durrës, 2001 Durrës, Albania Email: golemiela31@yahoo.com *Corresponding author Abstract: The latest trend of companies is that of fragmenting their production across several countries as a cost-saving policy. The selection of an optimal location for the fragmentation of the production depends on the economic, fiscal and institutional factors. This paper examines the main factors that influence the process of delocalisation of Italian companies in the Balkans. The results suggest that the work cost and productivity of the hosting country encourage the Italian enterprises to fragment their production in the given country. The empirical results of this study also suggest that institutional factors such as rule of law and corruption have a positive and significant correlation in the delocalisation. Finally, this study empirically examines the impact of fiscal factors. The results suggest that Italian companies are not influenced by the fiscal pressure of the host country. Keywords: international delocalisation of production; Italian companies; cost of production; delocalisation; productivity; corruption; rule of law. Reference to this paper should be made as follows: Muço, K. and Golemi, E. (2022) ‘The economic and institutional determinants in the international delocalisation of Italian companies’, Int. J. Trade and Global Markets, Vol. 15, No. 2, pp.135–148. Biographical notes: Klodian Muço is a Lecturer in the Research Centre on Economics of Transition Countries at Catholic University “Our Lady of Good Council”. He holds a BSc degree in Economics from Bergamo University, Italy. Following a MSc degree in Economic Organization and Business Development in International Markets from Bergamo University, Italy and a PhD in Political Economy from Insubria University, Italy. He was a Visiting researcher at Macerata University and at Bocconi University, also was a Post Doc from Fribourg University, Switzerland. Previously, he was Head of the Department in Political Economy and Tourism at the “Eqrem Çabej” University and Lecturer in the Faculty of Fastip at Aleksandër Moisiu University of Durrës. Copyright © The Author(s) 2022. Published by Inderscience Publishers Ltd. This is an Open Access Article distributed under the CC BY license. (http://creativecommons.org/licenses/by/4.0/) 136 K. Muço and E. Golemi Ela Golemi, PhD, is Professor of Macroeconomics and International Economics, member of Economics Department, University “Alexander Moisiu” Durrës. From 2016 to 2020, she has held the position of Dean of the Faculty of Integrated Studies with Practice and Vice Dean for Scientific Research at the Faculty of Business, University of Durrës. Her scientific activity focuses on sustainable economic development, financial stability and the Western Balkans’ economic policies for European Union integration, on which she has authored scientific articles and published them in reputable scientific journals. He has participated actively in many international scientific conferences, symposia and seminars in Europe and the USA. 1 Introduction In the recent years, the economic literature has paid special attention to the international fragmentation of production. Many studies have identified the growth of this phenomenon in question, its characteristics and the factors that lead to delocalisation of production (Ferrucci and Picciotti, 2017; Fratocchi et al., 2016; Cardullo et al., 2013; Popescu, 2013; Crestanello and Tattara, 2011; Pickles and Smith, 2011; Amighini et al., 2010). According to a study published in 2017, it turns out that three to five million manufacturing jobs have been lost because of offshoring. The report published by the European Restructuring Monitor (2016, p.31) affirms that during the period 2003–2016, 44.74% of jobs in the manufacturing sector of the European Union were lost by offshoring. The fragmentation process according to the report in question is focused on developed EU countries that also have high wages. According to Graziani (2001) and Yeaple (2003) the process in question is developed mainly for labour-intensive industries, which by fragmenting production to nearby countries with low input prices, can reduce unit costs of final products. Based on the above facts, the objective of this study is the analysis of factors that influence the selection of a country in the Balkan area by Italian companies at the moment when they decide to delocalise production process. Our analysis takes into account two groups of factors, economic and institutional. Our basic hypothesis is that: when Italian companies decide to delocalise they choose not only depending on the lower cost of labour input, but above all they take into account institutional factors such as rule of law and corruption. To confirm this hypothesis in this paper through a data panel, two empirical models will be made to see the impact of economic factors such as: labour cost, productivity and total tax rate, including institutional factors such as: rule of law, political stability and corruption, in the process of delocalisation of the Italian companies in one of the nine Balkan countries – Albania, Bosnia, Serbia, Macedonia, Montenegro, Bulgaria, Croatia, Rumania and Slovenia. The main results of this study show that Italian companies when they decide to delocalise production in one of the countries of the Balkan area, are not only influenced by labour costs, as affirmed by the vast majority of literature (Crestanello and Tattara, 2011; Amighini et al., 2010; Cietta, 2008; De Nardis and Traù, 2005; Helg and Tajoli, 2005), but they are also influenced by institutional factors such as the rule of law and corruption. Therefore, they prefer to evaluate direct and indirect costs in the complex. The economic and institutional determinants 137 The rest of the study is organised as follows: the next section presents the review of the empirical literature review and discusses the empirical model and cost estimation issues, while the results from the empirical analysis follow in Section 4, and finally Section 5 is a final conclusion of the above. 2 Theoretical predictions and literature review Over the last three decades, the progressive liberalisation of transactions, the progress in production technology, the reduction of transport costs and the logistical progress have all given opportunities and incentives to many different enterprises for the process of fragmentation of production and its geographical delocalisation. Today more and more we see that different companies produce intermediate products in different countries, or more precisely they fragment production. R&D, design, package, marketing, distribution, etc having as a primary objective the reduction of production costs and growth of comparative advantage (Nicita et al., 2013). This distribution of production processes depends on the geographical position and the nature of a product (UNCTAD, 2010), on the distribution of the power of the leading manufacturing firm (Gereffi, 1999; Altenburg, 2000) and the role of government institutions and incentive policies for foreign investment in a country (Sturgeon and Gereffi, 2012; Muço et al., 2018). According to traditional theory, there are two types of foreign direct investment (FDI) horizontal and vertical. Horizontal FDIs occur when firms produce similar goods and services in different countries to overcome transport barriers and reach the final consumer (Markusen, 2002). These types of investments are not the subject of our study. While vertical FDIs, have to do with the fragmentation of the production process in stages, to take advantage of differences in the price of inputs (Bronzini, 2010). This process is also known as offshoring. According to the study by Feinberg and Keane (2006) 19% of American multinationals have performed vertical FDIs in Canada to reduce production costs. This type of process according to Yeaple (2003) is highly developed since the companies operating in developed countries can reduce the unit cost of final products by shifting production to nearby countries that have low input prices. Various empirical studies have shown that in terms of production costs, labour cost is the primary factor that explains the international fragmentation of production (Crestanello and Tattara, 2011; Cietta, 2008; De Nardis and Traù, 2005; Helg and Tajoli, 2005). Reducing labour costs according to Giusti (2006) is an important factor that leads to increased competition in different countries, this often leads Italian companies to think that the delocalisation of production would make them more competitive in the market. This best motivates the fact that Italian companies which have delocalised production are mostly labour-intensive manufacturing companies operating in the textile and metal industry (Amighini et al., 2010). Most of these Italian companies started the delocalisation process in the early 1990s immediately after the German ones (Graziani, 2001). It is worth mentioning the fact that according to some statistics published by the Bureau of Labour in the USA (Bureau of Labor Statistics, 2012) it is noted that in China and India in 2003 the cost per hour was respectively 0.62 dollars and 0.81 dollars while in Italy, the target country of our study, it was 23.35 dollars. 138 K. Muço and E. Golemi It is worth noting that labour cost is only one of the factors that stimulates the delocalisation of production in a given country, as there are other factors such as: productivity (Pickles and Smith, 2011), distance, flexibility at work (Amighini et al., 2010; Rodrik, 1997), union pressure (Cardullo et al., 2013), similarities with the local system and culture (Powell and Di Maggio, 1983), linguistic knowledge of the host country, if they know the language spoken by the investor (Muço et al., 2018), political and institutional stability of the host country (Helpman, 1984), the level of corruption in the host country (Muço and Balliu, 2018), European Union membership, as member county companies want to relocate production other EU member states (Pickles and Smith, 2011). In addition, we need to highlight the differences in fiscal pressure between the developed countries and the countries that they choose to fragment production (Rabushka, 2003; Mitchell, 2004) as well as the fiscal incentives provided by FDIs host countries from developed countries (Muço et al., 2018). Production is also often delocalised due to the influence of new markets, for example, many Italian companies have delocalised production in China as it is the second largest retail market in the world and consequently sales of luxury products made in Italy are highly demanded (Ferrucci and Picciotti, 2017; Chevalier and Lu, 2009). According to institutional theories (Powell and Di Maggio, 1983), companies are driven by positive judgments of stakeholders who assess the appropriateness of strategic activities in order to develop their business activity. In other words, they are the ones who decide where the production should be moved and they are the ones who choose depending on the economic interests, the institutional environment of the host country and the fiscal pressure. According to North (1991) such enterprises tend to interact with other local firms but not only in order to improve their ability, to survive and thrive. Other factors that stimulate the delocalisation of production are the host countries which, knowing that FDIs transfers technology, offer them a number of advantages and have an impact on productivity growth (Amiti and Wei, 2006; Olsen, 2006). They tend to improve governance and regulate markets (Gereffi and Mayer, 2004), to reform the banking system, to reduce bureaucracy, to guarantee the free market (Demirbag et al., 2007) and to improve public administration (Batley and Larbi, 2004). Another factor is also the presence of other companies of the same nationality but not only. According to Popescu (2013), Italian shoe and textile manufacturers go to Timisoara because there is an important cluster and in this cluster there is a large presence of Italian companies. It should also be affirmed that during the last years there has been not only delocalisation of enterprises but also their return to the country of origin, i.e., reshoring (Ferrucci and Picciotti, 2017). This is done after a reassessment of the company to rebuild the production capacity in the country (Fratocchi et al., 2016) and also thanks to the intervention of the government. Aiming to cope with the economic crisis, the governments apply the perspective of re-industrialisation (Pisano and Shih, 2012). It is also important to mention the image of the production of a product in a developed country in contrast to the production in a third world country. This is especially true for luxury products in the textile sector. Returning to the origin country (reshoring) has also a positive impact on the increase of employment rate as delocalisation itself leads to unemployment (Crinò, 2009; Becker and Muendler, 2008; Corò and Volpe, 2006). However, the issue of unemployment or job loss due to delocalisation is not always supported in various studies (Falzoni and Tajoli, 2008; Amiti and Wei, 2004; Viesti and Prota, 2007). The economic and institutional determinants 139 3 Data and methodology The data used in this study are micro data, which make it possible to assess the impact of economic, fiscal and institutional factors on the delocalisation of Italian enterprises in one of the Balkan countries. To conduct this study we have created a data panel with data published by the Italian National Institute for Foreign Trade (ICE). The time series taken in this study include the period 2010–2018. To avoid data heterogeneity, we have not included other sources of information from different business associations for the delocalisation of Italian enterprises. Using them could help us expand the database and increase the number of observations but on the other hand we could have data inconsistencies. In this study we have included nine Balkan countries – Albania, Bulgaria, Bosnia, Croatia, Macedonia, Montenegro, Romania, Serbia, Slovenia. We have excluded Kosovo, Turkey and Greece from this study, due to lack of data and/or because they have a completely different economic structure compared to that of other countries included in the panel. The objective of this paper is the empirical verification of the impact that economic, fiscal and institutional factors have on the delocalisation of Italian enterprises in the Balkans. More specifically we will assess the impact that labour costs have on the delocalisation of production where according to many studies is one of the main factors that explains the international fragmentation of production (Crestanello and Tattara, 2011; Amighini et al., 2010; Cietta, 2008; De Nardis and Traù, 2005; Helg and Tajoli, 2005) and stimulates competition (Giusti, 2006). We want to verify the impact that there is a difference in fiscal pressure between the country of origin and the destination, in the delocalisation of production, where according to Rabushka (2003) and Mitchell (2004) taxes play an important role in attracting foreign investors. Last but not least, we will also empirically assess the impact that institutional factors have on the localisation of Italian investments in a particular Balkan country. In other words, we will assess the impact of corruption, rule of law and political stability of the host country on the withdrawal of Italian companies which according to various studies play an important role (Muço and Balliu, 2018; Helpman, 1984). To carry out this study we have selected as a dependent variable the Italian companies delocalised for every 100,000 inhabitants in the nine Balkan countries. As independent variables we have selected the economic and fiscal factors – Labour Cost, Productivity and Total Tax Rate and the institutional ones – Rule of Law, Political Stability, and Corruption. In order to have a thorough perspective of the study, it would be interesting to have data on the ‘loss’ of jobs in Italy to verify whether or not the results achieved by various studies on the verification of job losses from delocalisation can be verified (Crinò, 2009; Becker and Muendler, 2008; Corò and Volpe, 2006; Falzoni and Tajoli, 2008; Amiti and Wei, 2004; Viesti and Prota, 2007). However, it is impossible to collect reliable data. 140 K. Muço and E. Golemi 4 Empirical results In this section we discuss the empirical results of our study. As mentioned in the previous paragraph, our goal is to empirically highlight the economic, fiscal and institutional factors that influence Italian companies to delocalise to a particular country in the Balkan area. We set out to examine the main costs that should be borne by a company that delocalises production in a given country using indicators, such as, productivity, total tax volume, political stability and corruption. Figure 1 shows the trend of the delocalisation of Italian companies for every 100,000 inhabitants in a given country for the time period 2010–2018. The given graph shows that the country with the highest presence of Italian companies for every 100,000 inhabitants is Slovenia, a EU country. Slovenia is the country with the highest average salary in the Balkan area, about 1800 euros. But if we see data on turnover and employment of Italian companies in this country, Slovenia occupies the last place. Figure 1 Italian firms per 100,000 inhabitants (see online version for colours) Italian companies are more numerous in Romania, with about 53.6% of companies in total (6300) delocalised in the Balkan area (2018). The number of employees in Italian companies in this country reaches about 97,034 workers out of 190,000 workers in total in all the Italian companies located in the Balkan area. The annual turnover of Italian companies in Romania reaches about 7.3 billion euro out of an annual turnover of 14.6 billion in the Balkan area. In Figure 2, Romania seems to have a very positive growing trend for the period 2010–2013, whereas in the last two years the trend is decreasing. The two Balkan countries that attract the most Italian companies in the period in question are Serbia and Albania. In Serbia, the average number of Italian companies that have delocalised production is 460 with over 20 000 employees and about 2.2 billion in annual turnover. In Albania, on the other hand, the number of Italian companies is around The economic and institutional determinants 141 350, the number of employees is about a quarter of that of Serbia (7600) the annual turnover instead is about one fifth of that of Serbia 0.381 billion euro. Figure 2 Performance of some indicators for Western Balkan countries (see online version for colours) The graph shows clearly that Croatia is another EU country preferred by Italian companies. The number of Italian companies that have delocalised part of production to this country is over 460. The number of employees is around 14,000 and annual turnover is over 1.4 billion. By analysing the ICE data it is clear that the cost of labour is not the main factor that stimulates Italian companies to decide to delocalise to a particular country, if this were 142 K. Muço and E. Golemi true then the greatest concentration of Italian companies would be in Albania which is the country with the lowest level of average salary (426 euros). Below we see the other factors that may influence Italian companies to delocalise to one of the Balkan countries. In the first graph we see productivity by country, and there is a similar productivity trend from $27,240 in 2010 to $29,804 in 2018 in Albania; from $60,829 in 2010 to $71,589 in 2018 in Slovenia. Focusing on the value of productivity we see that Italy has the highest level of productivity ($92,296 for 2018) compared to all other Balkan countries where it delocalises production (the average of Balkan country for Output per worker (GDP constant 2011 international $ in PPP) in 2018 was $45,457, respectively ($29,804 in Albania; $39,101 in Bosnia and Herzegovina; $43,214 in Bulgaria; $57,475 in Croatia; $37,894 in North Macedonia; $48,123 in Montenegro $55,124 in Romania; $29,451 in Serbia; $71,589 in Slovenia). What is interesting about this graph is the fact that the EU countries have the highest level of productivity. The productivity of developing countries is obviously lower. Regarding the cost of hourly labour under PPP, it is much lower in Bulgaria ($13.06) and Albania ($4.62) where the average level of salaries is much lower than in all the Balkan countries including Bulgaria. Slovenia and Romania also have a relatively low hourly labour cost according to PPP. In the latter, the cost of hourly labour under PPP (respectively $27.16 and $15.11) has increased substantially in the time period 2011–2012. This period coincides with strong pressure from trade unions to improve working conditions and salary levels in Romania. An interesting fact to note is the case of Albania which despite having a very low salary level, the cost of hourly labour under PPP is similar with that of the Balkan countries. In the third graph we see the percentage of profit taxes. North Macedonia is the country with the lowest percentage level of profit tax until 2014. We need to highlight that according to the World Bank report for 2014 and 2015 the growth of real GDP for North Macedonia was 3.7% which is the highest in the Balkan area. The decrease in profit taxes has influenced the increase in FDIs in North Macedonia, which rose from 0.54% of GDP in 2014 to 2.95% of GDP in 2015 and 5.04% of GDP in 2016, 3.37% of GDP in 2017 and 5.12% of GDP in 2018 (WB, 2018). Croatia is the country with the lowest level of profit tax in the period in question. The last three graphs represent the institutional factors, such as, political stability, perception of corruption and rule of law. All these three indicators have been estimated. The values for these three indicators vary from high to low, that is, the lower the values, the less the perceived corruption, the better the political stability and the rule of law. For the three last graphs we can say that the sooner a country enters the EU, the better its institutional factors are. Albania and North Macedonia are the countries with the highest corruption index and lowest political stability. That is why these are the last two countries from those taken into consideration that have not yet opened the negotiations for accession to the EU, the decision for the opening of the negotiations for these two countries was taken in 24 March 2020. Below we see the empirical results of the impact of labour cost, productivity and total tax rate in percentage of commercial profit on the delocalisation of Italian companies in the Balkan area. The economic and institutional determinants 143 The variables of interest – productivity, labour cost, tax rate are assessed as differences from the Italian level, since it is this difference which should stimulate Italian companies to delocalise. From the Table 1 we see that delta labour cost (DLC) is correlated with Italian firms for 100,000 inhabitants. DLC have a positive and significant effect. The higher the cost of labour in a given country compared to Italy, the lower the number of Italian companies that delocalise production to that country. This result shows what has been said in the literature which we cited in the previous paragraphs, that low labour costs in a certain country encourage Italian companies to delocalise production to that country. The panel with DLC has an R = 0.26 which indicates 26% of the dependent variable is explained by the DLC. Table 1 The ‘economic/fiscal’ factors Dep. variables: Panel Panel Panel Italian firms per 100,000 inhabitants Fixed effects Fixed effects Fixed effects Delta Labour Cost –0.111* (constant 2011 PPP) (0.054) Delta Productivity 0.0002** (constant 2011 PPP) (0.000) Delta Total Tax Rate 0.314 (% of commercial profits) (1.144) Constant (average fixed effect) 7.22*** 16.30*** 8.19*** (0.416) (2.736) (0.369) Country Fixed Effects Yes Yes Yes F(1,8); Prob. > F 4.33; 0.07 9.02; 0.01 0.08; 0.79 R-sq within 0.26 0.13 0.00 R-sq between 0.09 0.13 0.05 R-sq overall 0.08 0.13 0.03 Countries 9 9 9 Years 6 6 6 Observations 54 54 54 Delta: Value Country i – Value Italy. Robust (clustered) standard errors in brackets. Sign: *: 10%; **: ù 5%; ***: 1%. The delta productivity (DP) has a negative but very small significant effect. The higher the productivity of labour in a country compared to Italy, the more Italian companies try to delocalise production to that particular country. In fact, from the descriptive statistics we know that productivity is lower than in Italy. Therefore, “the lower the negative difference compared to Italy is, the more numerous the Italian companies will be in that particular country”. In this model R = 0.13 which indicates 13% of the dependent variable is explained by the DP. The third independent variable that we take into consideration to explain the delocalisation of Italian companies is the Delta Total Tax Rate (% of commercial profits). This variable does not explain the dependent variable. The coefficient is not significant, 144 K. Muço and E. Golemi the R is very low and the F-stat is not significant. The explanation of the lack of significance of the variable in question could be the following: even though Italian companies delocalise production to the countries taken into consideration, still pay taxes in Italy and not in the country to which they have delocalised production. In Table 2 the dependent variable is again “Italian firms per 100,000 inhabitants”. As explanatory variables in this model serve the indicators of worldwide governance to understand the impact that good governance has on attracting Italian companies that want to delocalise production. The indicators we have chosen are: Political Stability (an index that measures the perception of the probability that the government will be destabilised or overturned by unconstitutional or violent means, including political violence and terrorism); Rule of Law (perception of individuals of the respectability of rules in society, which in particular measures the degree of execution of a contract, property rights, performance of the police and the judiciary, and also the probability of the presence of crime and violence); Corruption – an index that measures the perception of the citizens of how corrupt government officials are. Table 2 The ‘institutional’ factors Dep. Var.: Panel Panel Panel Italian firms per 100,000 inhabitants Fixed effects Fixed effects Fixed effects Rule of law 5.51** (2.08) Political stability 1.32 (0.91) Corruption 0.109** (0.011) Constant (average fixed effect) 8.19*** 7.87*** 3.50* (0.041) (0.151) (1.531) Country fixed effects Yes yes yes F(1,8); Prob. > F 7.00; 0.03 2.08; 0.19 8.96; 0.02 R-sq within 0.32 0.19 0.32 R-sq between 0.19 0.38 0.12 R-sq overall 0.19 0.34 0.12 Countries 9 9 9 Years 6 6 6 Observations 54 54 54 Robust (clustered) standard errors in brackets. Sign: *: 10%; **: 5%; ***: 1%. From the results of the second model we see that Rule of Law has a positive and significant impact on the delocalisation of Italian companies to a particular Balkan country. The model has an R = 0.32 which explains that 32% of the dependent variable is explained by the independent variable Rule of Law. The second explanatory variable, political stability has an insignificant correlation with the dependent variable; the F-stat coefficient is insignificant. The economic and institutional determinants 145 The third variable, corruption has a significant and positive correlation with the dependent variable. The R also in this case is equal to 0.32 which explains that 32% of dependent variable is explained by the independent variable, corruption. If we see the model in its entirety, it seems that the impact of the explanatory variables Rule of Law and Corruption is contradictory. No, the truth is that Italian companies seek out countries with credible and effective public institutions, but prefer countries where government officials can be manipulated, i.e., that favour Italian companies through biased processes while at the same time operating within the limits of the law. 5 Conclusions In this paper we study the impact that economic, fiscal and institutional factors have on the delocalisation of Italian companies in one of the Balkan countries. Compared to previous empirical literature, our analysis has the advantage of micro- homogenised data obtained from the Italian Trade Inspector (ICE). In the first model, the empirical analysis conducted in this study showed that labour costs and productivity of the host country encourage Italian enterprises to delocalise production in that country. While in the second model, the empirical analysis showed that institutional factors such as rule of law and corruption have a positive and significant correlation with the delocalisation of Italian companies in the Balkans. In this paper we also examined the fiscal factors, tax rate in % of commercial profits. In this case the results suggested that Italian companies are not influenced by the fiscal pressure of the host country because even when they delocalise parts of production, given that the parent company is in Italy, they still pay taxes in Italy. Therefore, the level of taxation does not influence the choice of a place for delocalisation of production. Both the empirical analysis and the review of the theoretical literature, affirm in a way what the vast majority of the empirical literature says that the cost of labour in the complex is one of the main factors leading to the international fragmentation of production. The results of this study make an important contribution to the empirical economic literature. These results confirm that Italian companies when delocalising production do not take into account the level of taxation of a country. They generally consider the reduction in production costs per unit. And the investment guarantee in that country which depends on institutional factors. The empirical results also show a very interesting fact, that Italian companies that delocalise production are not negatively influenced by the level of corruption of the host country. This in a way means that Italian companies that delocalise production sometimes cope with corruption. As a result they that have a little corruption which sometimes serves to fight bureaucracy. 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