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The report provides a comprehensive analysis of the Global Tattoo Removal Market by types, applications, players and regions. This report also displays the 2014-2025 production, Consumption, revenue, Gross margin, Cost, Gross, market share, CAGR, and Market influencing factors of the Tattoo Removal industry in USA, EU, China, India, Japan and other regions.
Tattoo Removal Market Analysis by Players: This report includes following top vendors in terms of company basic information, product category, sales (volume), revenue (Million USD), price and gross margin (%).
Syneron Medical
Tattoo Removal Market Analysis by Regions: Each geographical region is analyzed as Sales, Market Share (%) by Types & Applications, Production, Consumption, Imports & Exports Analysis, and Consumption Forecast.
Southeast Asia
South America
South Africa
Tattoo Removal Market Analysis by Types: Each type is studied as Sales and Market Share (%), Revenue (Million USD), Price, Gross Margin and more similar information.
Tattoo Removal Market Analysis by Applications: Each application is studied as Sales and Market Share (%), Revenue (Million USD), Price, Gross Margin and more similar information.
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Some Points from Table of Content:
1 Tattoo Removal Market Overview
1.1 Product Overview of Tattoo Removal
1.2 Classification of Tattoo Removal
1.2.1 Type 1
1.2.2 Type 2
1.2.3 Type 3
1.2.4 Type 4
1.3 Applications of Tattoo Removal
1.3.1 Application 1
1.3.2 Application 2
1.3.3 Application 3
1.3.4 Application 4
1.4 Global Tattoo Removal Market Regional Analysis
1.4.1 USA Market Present Situation Analysis
1.4.2 Europe Market Present Situation Analysis
1.4.3 Japan Market Present Situation Analysis
1.4.4 China Market Present Situation Analysis
1.4.5 India Market Present Situation Analysis
1.4.6 Southeast Asia Market Present Situation Analysis
1.4.7 South America Market Present Situation Analysis
1.4.8 South Africa Market Present Situation Analysis
1.5 Tattoo Removal Industry Development Factors Analysis
1.5.1 Tattoo Removal Industry Development Opportunities Analysis
1.5.2 Tattoo Removal Industry Development Challenges Analysis
1.6 Tattoo Removal Consumer Behavior Analysis
2 Global Tattoo Removal Competitions by Players
2.1 Global Tattoo Removal Sales (Volume) and Market Share (%) by Players
2.2 Global Tattoo Removal Revenue (Million USD) and Share by Players (2017-2018)
2.3 Global Tattoo Removal Price (USD/Volume) by Players (2017-2018)
2.4 Global Tattoo Removal Gross Margin by Players (2017-2018)
3 Global Tattoo Removal Competitions by Types
3.1 Global Tattoo Removal Sales (Volume) and Market Share (%) by Types
3.2 Global Tattoo Removal Revenue (Million USD) and Share by Type (2014-2019)
3.3 Global Tattoo Removal Price (USD/Volume) by Type (2014-2019)
3.4 Global Tattoo Removal Gross Margin by Type (2014-20
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How to Catch Foreign Fish? FDI and Privatisation in EU Accession Countries Bruno Merlevede Koen Schoors Department of Economics and CERISE, Centre for Russian International Socio-Political and Economic Studies, Ghent University, Hoveniersberg 24, B-9000 Ghent, Belgium [email protected], [email protected] February 19, 2005 Abstract This paper presents a partial adjustment approach to foreign direct investment (FDI). In this framework the observed stock of foreign investment is the result of two driving forces. On the one the stock is pulled towards its equilibrium level, even without policy changes, on the other hand the equilibrium level itself is continuously altering by changes in its determinants. By means of a dynamic panel data analysis we examine the determinants of investment by old EU-members in ten countries of Central and Eastern Europe. Overall, our estimations suggest that the traditional variables, such as market potential, trade integration, and relative unit labour costs, are fairly stable as determinants of the optimal stocks of FDI in transition economies. Institutional development in all its forms is a robust determinant of the optimal level of FDI. The relationship between FDI and the privatisation process is complex. Non-direct privatisation schemes negatively affect the speed of adjustment towards the equilibrium, whereas current direct privatisation strategies positively affect the equilibrium level of FDI. Privatisation history increases equilibrium FDI, independently of the method applied. JEL Classification: F20, F23, P33 Keywords: foreign direct investment, privatisation, partial adjustment 1 1 Introduction Attracting FDI is high on the priority list of many policy makers because FDI is widely regarded as an amalgamation of capital, technology, marketing, and management, especially in developing economies. Policy makers therefore have a genuine intrest to know the factors that attract FDI. From a theoretical point of view it is necessary to identify the conditions under which foreign investment will take place, because of the costs inherent to entering new markets and producing abroad (Markusen, 1995). Although considerable work has been done, there is no consensus model providing the basis for empirical work. The questions and the analytical approaches to answer them are drawn from different subfields of economic theory. Some approaches stem from the larger field of macroeconomics, some relate to general equilibrium trade theory, and some are more closely related to the theory of the firm, the latter using the tools of game and information theory (see Markusen and Maskus, 2001). The macro-approach typically consists in estimating the effect of potential determinants of FDI by regressing some transformation of FDI on a set of independent variables which on theoretical grounds would likely affect the profitability of investment. These variables reflect or affect the local market potential, the cost of production, and the general business environment. Following the growing literature that relates institutions to economic outcomes, we add institutional development to the list of determinants. Institutions have become an important aspect of the locational advantages of a potential host country (see for example Bevan et al., 2004). We examine the determinants of foreign direct investment into the countries of Central and Eastern Europe (CEECs) by EU member states. Prior to 1990 the scope for FDI was extremely limited in Central and Eastern Europe. The sudden collapse of the central planning system opened these countries to foreign investment resulting in a continuous flow of investment to the CEECs. The specific nature of the transition process makes CEECs perfectly suited for analysing the impact of institutional changes on foreign investment. The considerable variation in the speed and the nature of in- 2 stitutional development across CEECs enables this analysis. Especially the organisation of the privatisation process of formerly state-owned enterprises deserves a closer look, for it has been explicitly used as an element in strategies to attract or prevent FDI. Hungary, for example, encouraged foreign involvement in the privatisation process by tailoring privatisation schemes to foreigners. Prospective EU membership and integration in the EU are another 'institution' that could be an important determinant of FDI in transition countries. Indeed, Baldwin et al. (1997) attribute the bulk of the gain from EU membership to increased investment, coming from both reduced domestic risk and increased FDI flows. Given the state of economic and institutional development, there exists an equilibrium level of foreign penetration in an economy. As FDI was zero at the outset of transition, it is unlikely that the optimal level would be reached at once. Therefore we think of FDI flows as an adjustment process towards an equilibrium level of the stock of FDI. The observed stock of FDI is the result of two forces. On the one hand the stock is evolving towards an equilibrium level even without policy and changes in other determinants, on the other hand the equilibrium level itself is continuously altered by changes in its determinants. We specify a partial adjustment model that nicely reflects the main features of the process of FDI inflows, namely i) investment takes time to adjust towards the equilibrium stock of FDI, ii) investment depends on the actual stock, and iii) the equilibrium stock itself changes with the state of development. To date the empirical literature has largely ignored the dynamic aspects of the FDI process in transition countries. Kinoshita and Campos (2003) and Carstensen and Toubal (2004) are the exceptions. Kinoshita and Campos (2003) analyse FDI inflows at the country level which results in a more limited number of cross-section elements. Carstensen and Toubal (2004) also consider bilateral flows from the EU to the candidate countries. We differ from their analysis by developing a partial adjustment model into a dynamic panel setup where we eventually allow the speed of adjustment to the equilibrium to be influenced by the choice of the privatisation strategy. The estimations are performed using a generalized method of moments (GMM) technique following Blundell and 3 Bond (1998). We further apply a finite sample correction to the two step standard errors as suggested by Windmeijer (2000). The structure of the paper is as follows. Section 2 describes some stylised facts of the transition process and the investment flows from the EU to Central and Eastern Europe. Section 3 develops a partial adjustment model of FDI and introduces the determinants of the equilibrium stock of FDI. The data and estimation procedure are discussed in section 4, while section 5 contains the results. Section 6 concludes. 2 FDI and transition Table 1 presents some macroeconomic figures for the year 2000 for the countries in our analysis. Poland has the largest inward stock of FDI, followed by the Czech Republic and Hungary. The other countries are far behind in absolute figures. Looking at per capita figures changes the ranking. The Czech Republic and Hungary are still on top of the list, but Poland drops to the fifth place, only just in front of Latvia and the Slovak Republic. From columns 2 and 3 one can at sight infer a positive correlation between income and stocks of FDI. This lends already some support to the market seeking hypothesis of investment. The correlation is far from perfect, however, so other forces must be in play as well. The FDI per capita figures further reveal that Bulgaria and Romania are the worst performers. This can be related to the other columns: both countries are perceived as more risky than the others (a higher score means a less risky country), and their transition index has fallen behind, which is also reflected by the somewhat smaller share of the private sector in GDP. This is a first indication that institutional development might be a relevant factor for attracting FDI. The average gross monthly wages are much lower in Bulgaria and Romania, ceteris paribus this should help them to attract more FDI. However, if lower wage levels correspond to lower productivity levels, they hold no advantage. On the other end of the wage levels, we find Slovenia with wages that are more than double of the second most expensive country, Poland. 4 FDI stock FDI stock per capita GDP per capita Monthly gross wage Private sector share Country risk Transition index Czech Republic Hungary Poland Slovakia Slovenia 21644 19804 34227 4634 2809 2107 1987 870 858 1413 5423 4636 4300 3752 9534 342 319 347 246 710 80 80 70 80 65 61.67 63.54 62.63 50.70 70.11 3.3 3.6 3.4 3.1 3.2 Estonia Latvia Lithuania 2645 2084 2334 1898 860 632 3761 3250 3252 302 236 252 75 65 70 55.02 52.60 50.45 3.3 2.9 3.1 Bulgaria Romania 2716 6480 398 290 1547 1649 125 130 70 60 41.13 35.21 2.8 2.7 Inward FDI stock in millions of USD, UNCTAD FDI Database; FDI stock per capita in USD, UNCTAD FDI Database; GDP per capita in USD, World Economic Outlook Database, IMF; Monthly gross wages in manufacturing in euro, ILO Handbook of Labour Statistics; Private sector share in GDP, EBRD Transition Report; Country Risk, Euromoney magazine; Transition index: average of EBRD reform indicators, EBRD Transition Report. Table 1: Overview of macroeconomic situation in 10 Central and Eastern European Countries Host Bulgaria Czech Estonia Hungary Latvia Lithuania Poland Slovakia Slovenia Republic 2000 2001 2000 2000 2000 2000 2000 2000 Source 1999 Austria Belgium Denmark Finland France Germany Italy Netherlands Portugal Spain Sweden UK 5.6 6.2 0.1 2.7 19.3 1.7 3.7 0.1 2.6 0.3 11.0 11.1 5.4 1.2 0.6 4.3 25.5 0.8 30.1 0.2 1.4 4.8 0.2 0.3 3.4 25.4 0.9 2.6 0.6 4.0 39.5 3.2 12.2 5.3 0.5 1.6 6.5 25.8 2.7 22.5 0.1 0.4 0.9 1.1 0.5 10.5 6.2 11.1 0.1 2.8 0.1 12.6 5.0 0.7 4.1 18.3 6.0 1.1 7.4 0.2 1.1 0.1 17.3 6.7 3.3 2.5 2.5 0.6 12.5 19.0 4.4 26.1 0.5 1.9 3.5 3.3 14.5 1.6 3.2 28.7 1.5 24.4 3.2 45.6 1.3 1.5 10.7 12.5 5.4 3.0 0.5 3.6 Total 53.3 85.4 80.1 79.6 48.9 63.0 80.1 77.1 84.1 US 12.0 6.5 9.5 Source: World Direct Investment Report 8.2 9.4 9.8 9.6 6.8 3.9 Table 2: Percentage of inward FDI stock in transtion countries originating from 12 EU-countries and the US 5 Already early in transition it became clear that most of the Central and Eastern European countries were redirecting their economy towards Western Europe and the EU. Their increasing integration with the EU resulted in a stream of FDI flows from the EU. This stream reflects a continuous adjustment towards a desired equilibrium stock of FDI by EU-countries in these newly emerging economies that almost since the start of transition have been expected to join the E(M)U sooner or later. Table 2 gives an overview of the importance of the EU countries as source countries for inward stocks of FDI in nine CEECs.1 The EU accounts for about 80% of the stock of inward investment in most countries. The exceptions are Bulgaria, Latvia and Lithuania. For Bulgaria, other important source countries -apart from the US in the last line- are Cyprus (9.6%), Russia (6.7%), Switzerland (3.8%) and the Bahamas (3.7%). For Latvia, Estonia and Russia are the other important sources (11.2% and 6.0% respectively). In the case of Lithuania, FDI is spread out more equally. Switzerland, Norway, and Estonia are the larger source countries, all three accounting for about 5% of the inward stock of FDI. Overall Germany is the most important investor in Central and Eastern Europe. The Netherlands are at least an equally important source for the top four of transition (Czech Republic, Hungary, Poland, and Slovak Republic), but only play a minor role in the other countries. Austria is an important investor in its neighbouring countries. The Baltic States are strongly linked with Scandinavian countries. Denmark, Finland and Sweden account for nearly 70% of the stock of FDI in Estonia, 30% in Latvia, and 42% in Lithuania. 3 A partial stock adjustment model Given the state of development of an economy, there is an equilibrium level of foreign presence. We think of FDI flows as reflecting an adjustment process of the stock of FDI towards this equilibrium. Since the state of development of the transition economies has been changing, the equilibrium must have been changing as well. A partial stock adjustment model nicely encompasses 1 There were no data available for Romania. 6 these features. In a partial adjustment model i) the rate of growth of a variable Y is -ceteris paribus- proportional to the stock of Y and ii) the rate of growth is -ceteris paribus- proportional to an equilibrium value, Y ∗ . The law of growth of Y can be written as: dY = βY (Y ∗ − Y ) dt 0<β<1 (1) Some rewriting shows that the percentage rate of growth is a linear decreasing function of Y : d ln Y dY = = β (Y ∗ − Y ) Y dt dt (2) Chow (1967) indicates that an analytically more convenient expression is d ln Y dt = α (ln Y ∗ − ln Y ) ⇔ dY = αY (ln Y ∗ − ln Y ) dt 0<α<1 (3) (4) The percentage rate of growth is now a linear decreasing function of ln (Y ). The solution to the differential equation (1) results in the so-called logistic curve, while the solution of the differential equation (4) gives the so-called Gompertz or loglog curve. In further stages of the process, i.e. for larger values of Y , a given increment in Y will dampen the rate of growth more for the logistic hypothesis than for the Gompertz hypothesis and the Gompertz rate of growth will be closer to a constant than the logistic rate of growth. A further difference between the two formulations arises in terms of the point where the maximum growth rate is reached. By setting derivatives with respect to Y equal to zero, one can infer that the maximum growth rate occurs at Y = 0.5Y ∗ for the logistic case and Y = e−1 Y ∗ = 0.37Y ∗ for the Gompertz case. Furthermore the growth driven by (2) is symmetric around 0.5Y ∗ , while the decline in the Gompertz case is much more gradual. Although this is more in line with adjustment processes in reality, the main 7 reason to prefer the Gompertz formulation is its analytical convenience. The analytical convenience of the Gompertz formulation rests on the fact that we can replace (3) relatively easy by its discrete version. The latter implies approximating the derivative of ln (Y ) by ln (Yt ) − ln (Yt−1 ) and the existing stock Y by Yt−1 (see Chow, 1967 and Cheng and Kwan, 2000). Replacing Y with the stock of FDI, we obtain d ln F DIi,t dt dF DIi,t dt = α (ln F DIi∗ − ln F DIi,t−1 ) (5) = αF DIi,t (ln F DIi∗ − ln F DIi,t−1 ) (6) (5) says that the percentage change of the stock of FDI is proportional to the gap between ln F DIi∗ and ln F DIi,t−1 . Since d ln F DIi,t = dF DIi,t /F DIi,t , we can infer from (6) that the rate of change of the stock of FDI is proportional to the existing stock, holding the gap constant. Here we need to assume that the equilibrium level, F DIi∗ , is unaffected by F DIi,t .2 In the absence of other constraints, the equilibrium level of the stock of FDI would otherwise be either zero or infinity. The term ln F DI ∗ − ln F DIi,t−1 implies that the self-reinforcing effect of F DIi,t diminishes as the actual stock approaches the equilibrium stock. It thus captures a process of gradual adjustment towards the equilibrium stock and is in line with the investment literature, which argues that the desired capital stock is attained gradually rather than instantaneously (Cheng and Kwan, 2000). The actual path of adjustment is thus the result of the interaction of the positive feedback effect with the distance between the stock of FDI and its equilibrium. For empirical purpose we switch to the discrete version of (5) and approximate the derivative of ln (F DIi,t ) by ln (F DIi,t ) − ln (F DIi,t−1 ). With fdii,t = ln (F DIi,t ) we have fdii,t − f dii,t−1 = α (fdi∗i − fdii,t−1 ) fdii,t = (1 − α) f dii,t−1 + αf di∗i 2 In order to have agglomeration effects the opposite should hold. 8 (7) (8) From (8) we can infer that the observed stock of FDI at time t reflects the impact of two driving forces. First, the 'positive feedback' effect propels the stock towards its equilibrium level, even without changes in other determinants. Note that for the process to be stable (1 − α) needs to be a positive fraction. Second, during the course of transition the determinants of the equilibrium level of FDI have changed. Consequently, the equilibrium level itself must also have shifted over time, and should get a time indicator, i.e. fdi∗i,t . In order to be able to estimate (8) we need to specify the determinants of equilibrium FDI. According to the type of FDI different factors might be decisive for the choice of location. Resource seeking investors will be attracted to locations with ceteris paribus low labour costs and good access to transport possibilities to the relevant markets. For market seeking investors local demand factors will be more important. Other factors might matter to both types of investors. Generally, the relative profitability of different locations will be decisive for choice among them. The importance of the following variables has been highlighted by earlier work3 : the market size of the host country, the country's openness to trade, wage costs adjusted for the quality of labour, and the riskiness of a location (specially for emerging markets). Chakrabarti (2001) performed an extreme bound analysis for a large cross-section of countries and found strong support for the explanatory power of host country market size. Other determinants are more sensitive to the conditioning information set. Chakrabarti (2001) further finds that a country's openness to trade, followed by wage costs, is more likely to be correlated with FDI than other determinants. The specific nature of the transition process brings along some further less standard determinants. First of all the key institutions underlying a market economy had to be put in place. Since the speed and approach of the institutional development differed widely among CEECs, institutional de3 See e.g. Bevan and Estrin (2000), Bevan et al. (2004), Carstensen and Toubal (2004), Chakrabarti (2001) and references therein, Cheng and Kwan (2000), Garibaldi et al. (2001), Holland and Pain (1998), Kinoshita and Campos (2003), and Resmini (2000). 9 velopment might constitute a decisive factor in the location choice of foreign investors in the region. Because of the variation in institutional development, transition countries make an ideal environment to test the impact of institutional development on FDI-patterns. Especially the privatization of state-owned enterprises stands out as an institutional change that is very likely to have borne a considerable impact on FDI. The methods of privatisation varied widely across countries and embodied substantial differences in the openness of the process to foreigners. Three broad categories of privatization methods can be distinguished, namely insider privatization, voucher privatization and direct sales privatization. Insider privatization is not conducive to foreign investment as the local firm is 'sold' to a combination of management and employees. These insiders have been very reluctant and slow to transfer their controlling powers to outside owners (see for example Filatotchev et al., 1999, for Russia). Voucher privatization allows citizens to trade vouchers (which they received for free) for shares in companies at primary privatisation auctions. Citizens can do so directly or via intermediaries (for example the investment funds in the Czech Republic).In a later phase foreign investors can then buy shares from the new private owners on the secondary market. Direct privatization sales where state firms are sold for cash to the highest bidder have in general been most open to foreign participation. In many cases foreigners had equal access to the auctions, or even were explicitly targeted as potential bidders as was the case in Hungary (see State Audit Office, Hungary, 2001 for an overview of the role of foreigners in Hungary's privatisation process). Finally, during the 1990s, the European Community and its Member States progressively concluded agreements with ten countries of Central and Eastern Europe. Since EU membership implies certain standards in terms of macroeconomic stability, institutional and legal environment and political stability, the key announcements in the EU accession process may also have affected foreign investment. For example, lowered trade barriers between accession countries and the EU might be relevant for resource seeking investment. 10 4 Data and estimation procedure The dataset contains bilateral stocks of FDI in billions of 1996 EUR. The host countries are the eight new member states of the EU4 , Bulgaria and Romania. The source countries are twelve of the current EU member states.5 The data are drawn from the European Union Foreign Direct Investment Yearbook 2001 supplemented with data from the OECD International Direct Investment Statistics Yearbook. We do not have data for all possible country pairs and end up with 99 combinations. The data period covered is 1992-2000 for most of the cross-sections, but not for all. Depending on the explanatory variables used the total number of observations is about 600. As measure for market potential we use real GDP in EUR, calculated as GDP in USD multiplied by the euro-dollar exchange rate, deflated by euro prices. These series are drawn from the IMF International Financial Statistics database (IFS). The cost of labour in the host countries is measured by average monthly wages in manufacturing, converted to euro. Average monthly wages are obtained from the ILO handbook of labour statistics, exchange rates are taken from IFS. Given a certain discrepancy in labour quality across countries wage levels are probably not the right criterion for investors and should be corrected for the quality of labour. One may argue that foreign firms will be interested in wage levels rather than in unit labour costs because they bring their own productivity increasing technolgy with them. Unit labour costs, however also reflect how well workers will be able to cope with new machinery. Therefore we consider unit labour costs as an alternative to wages. Unit labour costs are calculated as average monthly wages divided by productivity, in turn calculated as GDP divided by employment. The latter again is taken from IFS. We expect a negative impact of unit labour costs. Given that we consider bilateral flows, we further transform the variable by making the ratio of host country unit labour costs to source country unit labour costs. The larger this ratio, the smaller 4 Czech Republic, Estonia, Hungary, Latvia, Lithuania, Poland, Slovak Republic, and Slovenia. 5 Austria, Belgium, Denmark, Finland France, Germany, Italy, the Netherlands, Portugal, Spain, Sweden, and the United Kingdom. 11 the difference between host and source country unit labour costs. As the ratio gets bigger, we expect less FDI. The expectation of a negative sign therefore remains valid. Gravity models of international trade suggest that the distance between two countries can serve as a proxy for transportation (and informational) costs. The smaller the distance, the larger the expected trade volume between two countries. With respect to FDI, distance between host and source may reflect opposing effects. The greater the distance, the more incentives there are to relocate production facilities to the host country and to replace exports with FDI. However, in case of resource seeking FDI with the intention of exporting to the source country distance will have the opposite effect. Therefore we abandon distance and introduce bilateral trade between host and source country as explanatory variable. This variable, labelled integration, is exports from source to host plus imports by source from host as a percentage of host country GDP. Bilateral exports and imports are taken from the IMF Direction of Trade Statistics. The variable measures the importance of the source country as trading partner for the host country and reflects the degree of integration with individual (old) EU-members. At the same time it also controls for the size of the source country, since other things equal the host country will have more bilateral trade with a larger source country. A significant positive coefficient indicates that for source countries that are more important trade partners, the stock of FDI of the source in the host is likely to be larger. Note that the variable has little to say about whether FDI and trade are substitutes or complements. Moreover, the substitution-complementarity issue is likely to differ across industries (Lipsey, 1991): complementarity stems primarily from increases in demands for intermediates in vertical relationships, and substitution emerges from trade displacement among final goods. Investment decisions in emerging markets are also influenced by country risks. Risk ratings are provided on demand by specialized firms. These ratings are quite comprehensive and cover a broad range of underlying economic and political performance indicators. To the extent that we control for these factors in the regression, risk perception should no longer matter. 12 Nevertheless it is interesting to see whether these ratings add to the explanatory power of our regressions. We use the average of the country risk ratings published twice a year by Euromoney. Because a higher value indicates less risk, a positive relation with FDI inflows can be expected. In the specific case of transition countries the perceived country risk is highly correlated with progress in reform. Resmini (2000) concludes that the path and the pace of structural reforms have been crucial for attracting FDI (her sample covers 1990-95). According to Kinoshita and Campos (2003) trade liberalization and a reduction in capital controls are most relevant to foreign investment among all the available indices of structural reform. If trade is positively associated with FDI, a more liberal trade regime will induce FDI. On the other hand, if FDI is motivated by avoiding trade restrictions, reduction of these restrictions will not induce more FDI. Restrictions to currency convertibility hamper import of inputs and repatriation of profits, phenomena that typically come along with FDI. In the empirical analysis we test for an effect of the progress in different areas of reform. In order to do so, the liberalisation indicators taken from the yearly Transition Report, issued by the European Bank for Reconstruction and Development (EBRD), are added to the regressors. With respect to progress in the privatisation process we use more detailed measures than the liberalisation indicator from the Transition Report. We use separate indices for insider, voucher and direct privatization. The variables take the value 1 if the method concerned was the primary privatization method in a given year, 0.5 if it was the secondary, and 0.25 if was the third method. The indicator takes into account whether privatization actually occurred or not. The data are taken from Garibaldi et al. (2001), and are updated with information from several recent issues of the Transition Report. The time-varying equilibrium level of FDI, f di∗i,t can then be written as f di∗i,t = β 0 Xi,t (9) where Xi,t is a vector of the determinants of fdi∗i,t discussed above. Substi- 13 tuting in (8) gives f dii,t = (1 − α) fdii,t−1 + αβ 0 Xi,t (10) This is equivalent to the following error-correction representation where the imposed restriction follows from the assumption of the partial stock adjustment model. ¡ ¢ ∗ ∆fdii,t = α β 0 Xi,t−1 − fdii,t−1 + αβ 0 ∆Xi,t For estimation we consider the following reparametrisation of (10). This is a dynamic panel regression with a lagged dependent variable on the righthand side. f dii,t = δf dii,t−1 + γ 0 Xi,t + uit (11) uit = η i + ν it The OLS estimator of (11) is inconsistent because the lagged dependent variable is positively correlated with the error term (η i + ν it ) due to the presence of the individual effects. Though the within estimator eliminates this source of inconsistency by transforming the equation to eliminate ηi , it introduces a non-negligible correlation between the transformed laaged dependent variable and transformed error term introducing a new source of inconsistency (see Nickell, 1981). Arellano and Bond (1991) propose to apply a GMM-estimator on the first-differenced version of (11). ∆f dii,t = δ∆f dii,t−1 + γ 0 ∆Xi,t + ∆uit (12) where the cross-section specific effects are eliminated by first-differencing. The transformed specification itself suggests an instrumental variables approach. f dii,t−2 is correlated with f dii,t−1 − fdii,t−2 , but not with ν it−1 under the assumption of no autocorrelation in the level residuals.6 Provided 6 The only further assumption required is that the initial conditions yi1 are uncorrelated 14 T ≥ 3, the two period lagged level of the dependent variable can be used to identify α. Arellano and Bond (1991) suggest the following extended list of instruments for the first differenced equations. More precisely, rather than using only f dii,T −2 as instrument for the first-differenced equation in period T , f dii1 , fdii2 , ..., fdii,T −2 are available as instruments. E (f dii,t−s ∆ν it ) = 0 t = 3, ..., T and s ≥ 2 (13) In the case of multivariate analysis the explanatory variables can be used as additional instruments. For strictly exogenous variables x, both past and future values are valid instruments. In the case of reverse causality, x is said to be only weakly exogenous or predetermined. Then only suitably lagged values of x qualify as valid instruments. This gives rise to the following moment conditions. For strictly exogenous variables E (xi,t−s ∆ν it ) = 0 t = 3, ..., T and all s (14) and for predetermined variables E (xi,t−s ∆ν it ) = 0 t = 3, ..., T and s ≥ 2 (15) The first-differenced GMM estimator has been found to have poor finite sample properties (bias and imprecision) when the lagged level of the series are only weakly correlated with subsequent first differences, so that the instruments available for the first-differenced equations are weak (Blundell and Bond, 1999). This is the case in our dataset as the correlation between ∆f dii,t and fdii,t−1 is only -0.36.7 Blundell and Bond (1998) suggest to augment the first-differenced moment conditions by the following level moment with the subsequent disturbances, i.e. E (yi1 ν it ) = 0 for i = 1, ..., N and t = 2, ..., T 7 The correlation for the main explanatory variables is: -0.07 for GDP of the source country, -0.28 for relative unit labour costs, and 0.21 for the integration variable. 15 conditions to improve the efficiency of the GMM-estimator. E ((η i + ν it ) ∆f dii,t−1 ) = 0 for t = 3, ..., T (16) Level moment conditions for the explanatory variables can be added accordingly: E ((η i + ν it ) ∆xi,t−s ) = 0 t = 2, ..., T and all s (17) for strictly exogenous x, and for predetermined x E ((ηi + ν it ) ∆xi,t−s ) = 0 t = 3, ..., T and s ≥ 1 (18) The GMM estimation based on the moment conditions (13)-(18) can be performed in one step or in two steps. The difference between both estimators is that the one-step estimator is asymptotically efficient only under homoskedasticity of the ν it , while two-step estimator does not require homoskedasticity to be asymptotically efficient. Nevertheless, a lot of applied work has focused on the one-step GMM estimator rather than the two-step version because the two-step weight matrix depends on estimated parameters. This makes the usual asymptotic distribution approximations less reliable for the two-step estimator. Simulation studies have shown that the asymptotic standard errors tend to be much too small, or equivalently the asymptotic t-ratios much too big, for the two-step estimator, in sample sizes where the equivalent tests based on the one-step estimator are quite accurate. Windmeijer (2000) provides a formal analysis of the issue, and proposes a finite sample correction for the asymptotic variance of the twostep GMM estimator. We use the two-step estimator and present corrected standard errors.8 The overall validity of the moment conditions is checked by the Hansen (or Sargan) test of overidentifying restrictions. The null hypothesis of no misspecification is rejected if the minimized GMM criterion function regis8 In an analysis comparable to ours Carstensen and Toubal (2004) presents highly significant coefficients. As they do not deal with the issue of the standard errors, some caution is warranted. 16 ters a large value compared with a χ2 -distribution with the degree of freedom equal to the difference between the number of moment conditions and number of parameters. The key identifying assumption that there is no serial correlation in the ν it disturbances can also be tested. If the level residuals are indeed serially uncorrelated, then, by construction, the first-differenced residuals in (12) would follow an MA(1) process which implies first-order autocorrelation, but no higher order autocorrelation. Based on the firstdifferenced residuals, the Arellano-Bond m1 and m2 statistics test the null hypotheses of zero first- and second-order autocorrelation, respectively (see Arellano and Bond (1991) for further details). An insignificant m1 or significant m2 will issue warnings against the likely presence of invalid moment conditions due to serial correlation in the level residuals. 5 Empirical results Table 3 contains a first set of results. The tests for first and second order autocorrelation and the Hansen test for overidentifying restrictions are satisfactory in all cases. This holds with respect to the test statistics in tables 4, 5, and 6 as well. The displayed coefficients are based on (11). To infer the impact on the equilibrium level of FDI we need to divide the table entries by 1 minus the coefficient of lagged FDI. Specification [1] in table 3 present results for the more traditional model. In addition to the lagged stock of FDI, following from the partial adjustment specification, we use four variables as determinants of the equilibrium stock: GDP, relative unit labour costs, the risk indicator, and the integration variable. From specification [1] in table 1 we see that the lagged stock of FDI is significant both statistically and economically in explaining the current stock of FDI. The significant positive impact of GDP suggests that the market access mechanism is present. A 1% increase in GDP results in an increase of 0.317/(1-0.75)=±1.27% of the equilibrium stock of FDI. The integration variable is statistically significant and is positively signed. An increase in trade intensity between host and source is accompanied by an increase in the stock of FDI of the source in the host. An increase of 1%-point 17 FDIt-1 GDPt Integrationt [1] .750 [2] .702 [3] .700 [4] .709 [5] .712 [6] .698 [7] .704 [8] .693 [9] .699 (20.88) (15.86) (16.06) (17.34) (17.63) (16.34) (17.65) (14.46) (16.15) .317 .364 .367 .325 .349 .324 .349 .365 .384 (4.98) (4.63) (4.74) (4.19) (4.90) (4.37) (4.87) (4.40) (5.36) (4.06) (4.17) (4.29) (4.34) (4.37) (4.72) (4.57) (3.82) (4.38) .024 0.29 .028 .026 .028 .029 .029 .029 .029 Relative unit -.614 labour costt (-1.93) Riskt .153 -.724 -.790 -.765 -.743 -.771 -.741 -.863 -.908 (-1.93) (-2.14) (-2.33) (-2.29) (-2.31) (-2.32) (-2.28) (-2.35) .149 .156 .146 .144 .156 .143 .174 .033 (2.46) (2.17) (2.27) (2.46) (2.33) (2.43) (2.25) (2.54) (0.21) Privatisation insidert -.124 (-1.31) vouchert -.137 (-1.46) directt nondirectt .195 .215 .199 .188 .218 .178 .192 .201 (2.21) (2.50) (2.24) (2.15) (2.52) (2.17) (2.06) (2.33) Extra market potentialt† -.145 -.065 -.082 -.064 -.068 -.154 -.163 (-2.00) (-0.91) .017 (-1.27) 1.666 (-0.81) .018 (-1.05) 3.905 (-2.13) (-2.17) (1.04) (0.58) (1.92) (1.67) EU accession Essen .527 Agenda 1 .073 (0.83) (1.23) Agenda 2 .033 (0.46) N M1 M2 627 -4.05 -1.13 (0.26) Hansen χ² 93.32 (0.64) 627 -3.93 -1.10 627 -3.89 -1.10 627 -3.89 -1.08 (0.27) (0.27) (0.28) 93.34 93.55 91.51 (0.64) (0.64) (0.97) 627 -3.92 -1.09 627 -3.87 -1.13 627 -3.90 -1.12 (0.28) (0.26) (0.26) (0.25) (0.29) 93.67 95.23 91.25 93.64 93.47 (0.96) (0.95) (0.97) 627 -3.83 -1.15 (0.63) 627 -3.93 -1.05 (0.63) †Extra market potential: [4] sum of GDP of neighbouring countries; [5] distance weighted sum of GDP of neighbouring countries; [6] 'infrastructure' weighted sum of GDP of neighbouring countries; and [7] distance and 'infrastructure' weighted sum of GDP of neighbouring countries; Table 3: Basic results in trade integration is associated with an increase of about 0.096% of the stock of FDI. Relative unit labour costs have the expected impact. As the gap between host and source country unit labour costs becomes smaller, i.e. an increase in the relative unit labour costs, the stock of FDI is negatively affected. If for example the relative unit labour costs increase from 0.4 to 0.5, the equilibrium stock of FDI decreases with 0.24%. The risk variable is significant and has the expected sign. An increase in the risk variable with 1%, i.e. a reduction of the risk, increases the stock of FDI with about 0.612%. 18 In [2] we add the privatisation strategy used by the source country to the explanatory variables. We consider three categories of privatisation: direct, voucher and insider privatisation. Direct privatisation has a significant positive impact on FDI, whereas insider and voucher privatisation are negative but not significant. Because point estimates are not that different we reran the regression combining voucher and insider privatisation into the category non-direct privatisation. Specification [3] seems to suggest that countries that used a non-direct method as primary strategy on average have a logarithmic current equilibrium stock of FDI that is 0.58 lower, or a stock that is 1.79 billion EUR lower. Alternatively, this can be interpreted that nondirect privatisation as secondary method reduces the positive impact of the direct strategy that has been used as primary method. Though significant here, further results cast some doubt on the robustness of this finding. Specifications [4] to [7] test for an additional dimension of a country's market potential. In [4] and [5] we add the sum of the GDPs of the neighbouring transition countries to the other left hand side variables, the difference between [4] and [5] is that in [5] the respective GDPs are weighted by the inverse of the distance between the host country capital and the neighbour countries' capitals. While the conclusions with respect to the core variables arising from [3] remain unaffected, the extra market potential does not seem to add to a country's attractiveness. In [6] and [7] we use infrastructure as an additional weight to determine the potential arising from neighbouring countries. Infrastructure is defined as the ratio of kilometers of paved roads over country surface. The underlying assumption is that countries that are connected through a better road network are more easily accessible and therefore constitute a bigger market potential. In [6] the infrastructure weighted GDP of neighbouring countries is significant at the 5%-level. In [7] the distance and infrastructure weighted additional market potential is significant at the 10%-level. The main conclusions with respect to the other variables are unaffected.9 9 We also tested the EBRD index of trade and foreign exchange, import duties, and taxes on international trade as other possible weights along the lines of infrastructure. These were never significant but again left the core (qualitatively) unaffected. 19 Finally, in [8] and [9] we introduce EU integration announcement variables. The variables AG1 and AG2 in [8] reflect the division between first and second wave accession countries, identified in the Agenda 2000 document of the European Commission. The decision was taken at the Amsterdam 1997 IGC. AG1 is a dummy variable that takes the value 1 in the period 1997-99 for the first wave countries, AG2 is defined along the same lines but for second wave countries.10 Both variables are not statistically different from zero. Noteworthy is that AG1 is much larger and closer to significance than AG2. The ESSEN-variable in [9] reflects the launch of the pre-accession strategy at the Essen European Council in December 1994. The variable takes the value of 1 from 1995 onwards. As can be seen from table 3, we neither find a significant impact for this variable. This is in line with Bevan and Estrin (2000) who find no announcement effects for the level of FDI. Only after switching to changes in inflows and considering only announcement effects for Visegrad countries they find some impact. Does this mean that EU integration bore no effect at all on FDI? Clearly not, EU integration probably affected institutional development (think of the Copenhagen criteria). Moreover in this sample we only have data on accession countries and no other transition countries that integrated less with the EU.11 Furthermore, almost immediately after the start of transition it became clear that the countries of Central and Eastern Europe would, if not join the EU, than at least focus on the EU-countries as main trading partners and ease trade relations with the EU. Therefore our panel may be too limited to observe an effect. In table 4 we investigate the relationship between privatization and FDI more thoroughly. Since most of the enterprises were state-owned at the outset of transition, their privatisation potentially offered opportunities for brownfield FDI. A broad array of privatisation techniques was used across countries. During transition, countries switched methods or used combi10 The first wave countries are the Czech Republic, Estonia, Hungary, Poland, and Slovenia; the second wave roup consists of Bulgaria, Latvia, Lithuania, Romania, and the Slovak Republic. In 2000 eight of the ten applicants were announced to be entering the EU in 2004. The difference between first and second wave then disappears. Bulgaria and Romania will enter the EU in a later stage. 11 This is also the case in Bevan and Estrin (2000). 20 nations of methods. As we confirmed in table 3 not all methods allowed for FDI equally well. Clearly, not only current privatisation efforts bear an impact on the equilibrium stock, but the entire history of the privatisation process is likely to influence the current (equilibrium) level of the stock of FDI. Therefore we introduce the cumulative direct and non-direct indices, one period lagged to account for history. From [1] in table 4 one can infer that both the direct and non-direct privatisation history have a significant positive impact. Since we cannot reject their impact to be equal, we reestimate with [2] as result. Privatisation history, independent from the method used, has a positive impact on the stock of FDI. This probably reflects that privatisation is only the first step in a series of changes in ownership, so that eventually the opportunities for foreigners to invest are no longer related to the privatisation method used. This is in line with the findings of Frydman et al. (1996) that not the privatisation method per se, but the resulting ownership type is decisive for firm performance. The relationship between FDI and privatisation may be even more complex. We did not find a concurrent impact of non-direct privatisation. Nevertheless, voucher and insider privatisation schemes may have served as a dissuasive signal, beacuse they were partly induced by the fear of selling out to foreigners. This may lead foreign investors to postpone or even restrain them from their planned investment. Furthermore, non-direct methods resulted in natives owning the firms. Especially insider privatisation resulted in a sort of entrenchment as insiders clung to the control over the firm and blocked restructuring. New investors will then also be less eager to invest because the scope for positive externalities from domestic firms is smaller. This suggests that rather than affecting the equilibrium itself, non-direct methods of privatisation slow down the adjustment to the equilibrium. We test this by transforming (11) as follows, where we also allow for the possibility direct privatisation schemes serves as a positive signal to foreign investors, speeding up adjustment to equilibrium. 21 FDIt-1 [1] .628 (11.57) [2] .626 (11.86) FDIt-1*direct Integrationt Relative unit labour costt Riskt Privatisation directt nondirectt Cumulative directt-1 Cumulative nondirectt-1 Cumulative direct-nondirt-1 [4] .694 (13.24) (10.75) -.007 -.011 (-0.32) FDIt-1*nondirect GDPt [3] .654 -.038 (-1.99) [5] .642 (11.81) (-0.64) -.023 (-2.07) -.041 (-2.62) .434 .432 .421 .407 .437 (4.72) (4.78) (5.38) (4.87) (4.64) .038 (4.44) .037 (4.29) .040 (4.20) .036 (3.62) .039 (3.91) -1.189 -1.260 -1.316 -1.076 .127 .150 .161 .110 .130 (1.66) (1.94) (2.53) (1.71) (1.72) (-2.85) .165 (1.83) -.007 (-0.10) (-2.85) .199 (2.13) -.058 (-0.74) (-2.78) .179 (-2.36) .218 (1.78) (2.00) (-0.08) (0.20) -.007 .016 -1.180 (-2.18) .224 (2.03) -.027 (-0.33) .062 (2.26) .057 (2.35) .055 .053 .052 .050 (2.66) (2.96) (2.60) (2.44) N M1 M2 579 -3.70 -1.10 579 -3.70 -1.11 579 -3.73 -1.18 579 -3.76 -1.04 579 -3.64 -1.19 Hansen χ² 91.60 93.94 93.50 92.79 93.77 (0.69) (0.62) (0.95) (0.95) (0.60) (0.27) (0.27) (0.24) (0.30) (0.24) Table 4: FDI and privatisation schemes f dii,t = δ (1 + κ1 nondirectt−1 + κ2 directt−1 ) f dii,t−1 (19) 0 +γ Xi,t + εit ⇔ f dii,t = δfdii,t−1 + δ κ1 nondirectt−1 fdii,t−1 (20) +δ κ2 directt−1 f dii,t−1 + γ 0 Xi,t + εit Columns [3] and [4] in table 4 present results. They confirm our hypothesis that the use of non-direct methods slows down adjustment. The point estimate is small but significant. The coefficient of lagged FDI varies between 0.6 and 0.7 and is reduced by about 0.04. Direct privatisation does 22 not seem to affect the speed of adjustment. Results with respect to the other variables remain unaffected. In column [4] we consider privatisation strategies of the last 2 years, rather than just last year. The dampening impact on the speed of adjustment is now significant at the 5%-level. Since the no privatisation observations are limited, the correlation between direct and non-direct is fairly high, therefore [5] excludes the impact of direct privatisation on the speed of adjustment. The significance level of the interaction term increases to the 1%-level. Summarizing, our evidence suggests that current direct privatisation has an immediate positive effect on the equilibrium level of FDI, while current non-direct privatisation negatively slows down adjustment to equilibrium. Privatisation history positively affects the equilibrium level of FDI independently of the method used. Following the increasing literature that relates institutions to economic outcomes, institutions increasingly are stressed as potential locational advantages (see e.g. Kinoshita and Campos, 2003, Bevan et al., 2004). The risk variable already picked up the general institutional context to some extent. In the previous section we also elaborated on the complex relationship between FDI and privatisation, one of the important institutional reform areas. However, the entire institutional framework of the socialist economies had to be rebuilt from scratch. This process resulted in wide variety of approaches across countries. The EBRD provides indicators of progress in different areas of institutional reform in its yearly Transition Report. This allows us to test which institutions matter to foreign investors and which not. We therefore replace the risk indicator with various indicators of reform. Since foreign investors face costs for adaptation to an incomplete institutional environment, we expect the forerunners to have attracted more investment. In addition to the average level of reform we test for the impact of reform in the following areas: prices, trade and foreign exchange, competition policy, banking reform, and reform of non-banking financial institutions. Table 5 presents results for these different institutions. The average reform indicator used in column [1] is a simple average of the EBRD indicators, excluding the 23 FDIt-1 FDIt-1*direct FDIt-1*nondirect GDPt Integrationt Relative unit Labour costst Privatisation directt nondirectt cdirnondirt-1 Institution† [1] .622 [2] .680 [3] .661 [4] .670 [5] .673 (12.13) (13.58) (12.22) (12.10) (14.33) -.011 -.019 -.002 -.010 -.016 (-0.48) -.039 (-2.26) (-0.84) -.042 (-2.58) (-0.08) -.037 (-1.94) (-0.46) -.042 (-2.29) (-0.71) -.041 (-2.20) [6] .691 (13.02) -.012 (-0.48) -.043 (-2.28) .423 .389 .422 .410 .429 .451 (5.13) (5.14) (5.24) (4.65) (5.75) (6.66) .039 .037 .039 (3.82) (3.72) (4.01) -1.119 -1.663 -1.140 (-2.37) .183 (1.90) -.009 (-0.11) .040 (2.18) .506 (-4.07) .127 (1.26) -.025 (-0.33) .044 (2.36) .912 (-2.71) .202 (1.94) .004 (0.05) .047 (2.60) .352 .039 (3.62) -.720 (-1.92) .242 (2.35) .027 (0.35) .039 (1.88) .301 .039 (4.39) -.970 (-2.30) .171 (1.60) -.019 (-0.24) .036 (2.05) .416 .038 (3.68) -.567 (-1.75) .302 (2.58) .080 (0.93) .051 (2.18) -.177 (2.05) (3.71) (2.32) (1.78) (1.82) (-0.80) N M1 M2 579 -3.73 -1.07 579 -3.85 -1.02 579 -3.78 -1.03 579 -3.72 -0.98 (0.33) 579 -3.81 -1.18 (0.236) 579 -3.79 -1.09 Hansen χ² 91.44 89.12 93.38 92.57 91.03 90.05 (0.96) (0.97) (0.94) (0.95) (0.96) (0.97) (0.28) (0.31) (0.30) (0.28) Institutions used in: [1] Average refom (excl. privatisation) ; [2] Price reform; [3] Trade & foreign exchange reform; [4] Competition policy reform; [5] Banking reform; and [6] Reform of non-banking financial institutions † Table 5: FDI and institutional development indicators for small and large scale privatisation since we already extensively control for privatisation efforts. We find a significant positive coefficient. An increase of 1% in the level of average reform is associated with an increase of 1.34% in the stock of FDI. This points to the crucial role of the stage of development of institutions in attracting FDI, for in quantitative terms the point estimate of the coefficient implies a large positive contribution to FDI. The creation of markets has been one of the core elements of the transition to a market economy. In this respect, the liberalization of prices in both domestic and international markets was one of the crucial reform steps. As foreign investors usually prefer to operate on competitive domestic markets, price liberalization creates new business opportunities for them. 24 The abolition of exchange restrictions and multiple exchange rates allows to repatriate profits and reduces transaction costs.12 For both price reform and trade & foreign exchange reform, we find strongly significant positive coefficients (see columns [2] and [3]). This reflects that it is more interesting to invest in markets that have been liberalised and where there is free competition. Further, bureaucratic interference in business transactions that is subject to clear rules and regulation reduces institutional uncertainty. This applies notably to competition policy, which is important to protect consumers but can also be (ab)used to inhibit foreign entry. Regulatory policy is of particular concern for investors in industries with incumbent national monopolists (for example telecommunications). As old monopolies are broken, new possibilities are offered to foreign investors. Initially neglected, the design and implementation of competition policy has proven to be a complex process, that lagged the liberalization of markets for goods and services. In addition to the mere existence of rules, enforcement is necessary as well. Weak enforcement of regulatory policies tends to favour incumbent firms or firms with access to political and bureaucratic decision makers. Changes in competition policy therefore may change the relative competitiveness of firms operating in a given market and thus provide opportunities for entry of foreign firms with a competitive advantage. The results in [4] show a positive effect of improvements in competition policy. It is significant at the 10%-level. Progress in establishing financial infrastructure and capital markets facilitates access to complementary local financing for foreign investors and reduces transaction costs for local financial services. Further, better access to local finance helps to reduce the exposure to the exchange rate risk. A better financial architecture reduces the risk concerning the stability of the payment system and the risk of a banking crisis. Local customers are also more likely to gain access to bank credit. This can accelerate demand for goods that are often bought on credit, e.g. up-market consumer durables. Financial reform should thus increase business opportunities for foreign in12 Established foreign-owned firms that benefit from barriers to entry, however, will oppose this type of reform. 25 FDIt-1 FDIt-1*direct FDIt-1*nondirect GDPt Integrationt Relative unit labour costt Riskt Privatisation directt nondirectt Cumulative direct-nondirt-1 [1] .673 [2] .660 [3] .714 (12.77) (11.12) (15.64) -.017 -.004 -.004 (-0.71) (-0.17) -.043 -0.38 (-2.31) (-2.12) (-0.14) -.037 (-1.76) [4] .756 (18.32) -.015 (-0.51) -.041 (-1.88) .405 .418 .429 .272 (4.98) (5.13) (6.20) (4.19) .038 .041 (3.96) (3.71) -1.306 -1.228 (-2.71) (-2.60) .034 -.028 (4.18) (-0.54) (-2.21) (-1.64) -.107 -.579 .257 .148 .222 .222 (2.07) (2.67) (1.94) (2.15) .204 .181 (2.00) (1.74) .010 -.006 (0.13) (-0.07) .045 .041 .179 .139 (1.85) (1.53) (-0.08) (0.46) -.006 .014 .033 .026 (2.59) (2.33) (1.02) (1.49) N M1 M2 579 -3.80 -1.07 579 -3.71 -1.08 533 -3.94 -1.11 579 -4.01 -1.25 Hansen χ² 89.52 (0.29) (0.28) 87.90 (0.27) 91.94 (0.21) 92.88 (0.97) (0.98) (0.99) (0.95) [1] uses political risk instead of total risk; [2] uses the private sector share in GDP instead of risk; [3] uses skill-corrected wages instead of relative unit labour costs; and [4] includes the GDP of the source country instead of bilateral trade as a percentage of host country GDP Table 6: Additional checks by replacing core variables with suitable proxies (proxies are highlighted in grey) vestors. We find that banking reform in [5] is significant at the 10%-level. Consequently, a smoother working financial sector increases the attractiveness of a location. Reform of non-banking financial institutions, on the other hand, is of no importance to foreign direct investors as appears from [6]. We make a final round of robustness checks by replacing some of the core variables with suitable proxies. In column [1] of table 6 we replace our comprehensive risk indicator with its subcomponent that only reflects political risk. Our previous results are confirmed. We already indicated that the risk variable to a large extent accounts for progress in the transition to a market economy as well. In table 5 we tested the effect of progress in different 26 reform areas on FDI. In column [2] of table 6 we propose another variable that proxies progress in market reform. The private sector share in GDP (taken form the EBRD Transition Reports) not only measures progress in reform but probably introduces a further element in the sense that investors find it more attractive to do business with private firms. The private sector share exhibits a significant, positive relationship with the stock of FDI. Results with respect to the other variables are unaffected with the exception of the measure for direct privatisation, which is now borderline significant at the 10%-level. This is not surprising in the sense that current privatisation implies an immediate increase in the private sector share. Estimation [3] replaces the relative unit labour costs with a skill corrected wage measure. The latter is constructed as wages in euro divided by a skill measure, in 3 +EDU 2 x is gross education enrollturn defined as EDUEDU 3 +EDU 2 +EDU 1 where EDU ment with x = 3 denoting tertiary education, 2 secondary education, and 1 primary education. The proxy is significant and has the expected negative sign. The effect of non-direct privatisation on the intensity of the speed of adjustment is still significant, but only at the 10%-level. Privatisation history loses significance. Finally, in [4] the integration variable is replaced by the real GDP of the source country in euro. Source country GDP itself is insignificant in explaining stock of FDI. The privatisation variables lose significance at conventional levels, except for the effect on the effect on the speed of adjustment that remains significant at the 10%-level. Relative unit labour costs are also no longer significant. Overall, our findings suggest that the traditional variables are fairly stable as determinants of stocks of FDI in transition economies. A general measure for progress in reform is also robust to variations in the other explanatory variables. The same holds for the impact of non-direct privatisation on the speed of adjustment of FDI to its equilibrium level. There are good indications that direct privatisation strategies and privatisation history contribute to higher stocks of FDI, although the evidence is not as convincing as for the impact on the speed of adjustment. 27 6 Conclusions Given the state of institutional and economic development, there is an equilibrium level of foreign involvement in an economy. The collapse of the central planning system initiated a flow of foreign investment to the CEECs. We think of FDI flows as an adjustment process towards the equilibrium level of the stock of FDI. The observed stock of FDI then reflects the impact of two driving forces. First, there is a 'positive feedback' effect that drives the stock towards its equilibrium level, even without changes in other determinants. Second, during the course of transition the determinants of the equilibrium level of FDI have changed. As a result the equilibrium level itself has shifted over time. A partial stock adjustment model nicely encompasses these features and gives rise to a dynamic panel estimation. We investigate the factors that hamper or encourage FDI for a dataset of bilateral stocks of FDI of old EU-members in ten CEECs. We combine a group of traditional factors with a group of institutional factors induced by the transition process. With respect to the traditional determinants, market potential and trade integration with the source country are positively related to the equilibrium stock of FDI. Higher relative unit labour costs vis-à-vis the source country are associated with a lower equilibrium level of foreign presence. Lower perceived riskiness is associated with more FDI. In the case of transition countries perceived riskiness to a large extent reflects progress in institutional development. 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Estrin (2000), The determinants of foreign direct investment in transition economies, CEPR Discussion Paper No. 2638 Bevan, A., S. Estrin and K. Meyer (2004), Foreign investment location and institutional development in transition economies, International Business Review, vol. 13, pp. 43-64 Blundell, R., and S. Bond, 1998, Initial conditions and moment restrictions in dynamic panel data models, Journal of Econometrics, vol. 68, pp. 29-52 Blundell, R., and S. Bond, 1999, GMM estimation with persistent panel data: an application to production functions, Institute for Fiscal Studies Working Paper W/99/4 Carstensen, K., and F. Toubal (2003), Foreign direct investment in Central and Eastern European economies: a dynamic panel data analysis, Kiel Institute for World Economics Working Paper No. 1143 Chakrabarti, A. (2001), The determinants of Foreign Direct Investment: Sensitivity Analysis of Cross-Country Regressions, Kyklos, vol. 54, pp. 89-114 Cheng, L, and Y. Kwan (2000), What are the Determinants of the Location of Foreign Direct Investment? The Chinese Experience, Journal of International Economics, vol. 51, pp. 379-400 Chow, G. (1967), Technological Change and the Demand for Computers, American Economic Review, vol. 57, pp.1117-30 Eurostat (2002), European Union foreign direct investment yearbook 2001, Filatotchev, I, Wright, M., Bleaney, M. (1999), Privatization, Insider Control and Managerial Entrenchment in Russia, Economics of Transition, vol. 7 (2), pp. 481-504. 29 Frydman, R., C. Gray, M. Hessel and A. Rapaczynski, 1999, When Does Privatization Work? The Impact of Private Ownership on Corporate Performance in the Transition Economies, Quarterly Journal of Economics, vol. 114(4), pp. 1153-91 Garibaldi, P., N. Mora, R. Sahay, and J. Zettelmeyer (2001), What moves capital to transition economies, IMF Staff Papers, vol. 48, pp. 109-45 Holland, D., and N. Pain (1998), The diffusion of innovations in Central and Eastern Europe: A study of the determinants and impact of foreign direct investment, National Institute of Economic and Social Research Discussion Paper No. 173 International Labour Office, Handbook of Labour Statistics, various issues Kinoshita, Y., and N. Campos (2003), Why does FDI go where it goes? New evidence from the transition countries, William Davidson Institute Working Paper No. 573. Lipsey, R. (1991), Foreign Direct Investment in the United States and U.S. Trade, NBER Working Paper 3623. Markusen, J. (1995), The boundaries of multinational enterprises, and the theory of international trade, Journal of Economic Perspectives, vol. 9(2), pp. 169-89. Markusen, J., and K. Maskus, 2001, General-equilibrium approaches to the multinational firm: A review of theory and evidence, NBER Working Paper No. 8334, 45p. Nickell, S. (1981), Biases in dynamic models with fixed effects, Econometrica, vol. 49(6), pp.1417-26 OECD (2001), International Direct Investment Statistics Yearbook: 19802000 - Edition 2001, Paris Resmini, L. (2000), The determinants of foreign direct investment in the CEECs - New evidence from sectoral patterns, Economics of Transition, vol. 8(3), pp. 665-89 State Audit Office Hungary (2001), Privatisation in Hungary 1990-2000, mimeo presented to the INTOSAI Working Group on the Audit of Privatisation, Budapest, June 2001 30 Windmeijer, F., 2000, A finite sample correction for the varaince of two-step GMM estimators Institute for Fiscal Studies Working Paper W/00/19 31
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Hystresis Behavior of Three-Story Steel Fralme with Concentric K-Braces Part 2 (Ultimate Lateral Shear Capacity) -U.S.- Japan Cooperative Research Program-.
T.Fukuta*1, H.Yamanouchi*2; March, 1987. 24p.
In this paper, we propose the design oriented method on the ultimate lateral shear capacity of the steel frames with concentric inverted V-shaped braces and verify its effectiveness by the test results of the half-scale steel frames, that were conducted under the U.S.-Japan Cooperative Research Program Utilizing Large-Scale Testing Facilities.
A part of this paper was submitted to ASCE Structures Congress, Sep. 15-18, 1986, at New Orleans, U.S.A.
The steel frame is modeled to be the moment-resisting frame portion consisting of beams and columns, and the brace portion with the pin-ended beam in the braced bay. The ultimate lateral shear capacity of the total frame is given by the summation of the ultimate lateral strength of the both portions. The strength of the moment-resisting frame portion is calculated by the limit analysis using the virtual work method. The strength of the brace portion is given by the summation of twice as much as the ultimate compressive strength of the brace in the post-buckling large-deflection range and the contributing strength of the braced bay beam to the lateral shear strength. The contribution of the braced bay girder is conservatively estimated by 2Mgp/h, where Mgp is the full-plastic moment of the beam and h is the story height.
This method is applied to the weak beam frame, which means that the mid-span of the braced bay beam will be pulled down and yielded by the vertical resultant force which applies to the mid-span of the beam in the braced bay caused by the braces in the post-buckling, and to the frame where the first mode of vibration will fully affect its ultimate lateral shear capacity.
The ultimate lateral shear capacity by the method was confirmed to be a good approximation on the lateral shear strength of the half-scale test frames even in the large-deflection range.
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Sulphide-rich sediments, stromatolitic limestones and tidal-flat deposits in the late Archaean (2.7 Ga) Manjeri and Cheshire Formations, Belingwe greenstone belt, Zimbabwe show evidence for complex and extensive prokaryotic mat communities, including (1) shallow-water coastal sulphur mats; (2) mats, probably in somewhat deeper water; (3) nearby stromatolites that lived by oxygenic photosynthesis in shallow coastal settings. Petrological and geochemical (rare earth element; REE) evidence, coupled with high-resolution stable isotope results, identifies several complex interdependent metabolic consortia of bacteria and archaea. These microbial consortia would have exchanged nutrients and products both locally within prokaryotic mats and more widely via the waters of the Belingwe basin. This isotopic, sedimentological and REE evidence for a complex ecology of bacteria and archaea is consistent with metabolic inferences from rRNA phylogeny and is direct evidence that a diverse prokaryotic community, managing carbon on a global scale, had evolved by the late Archaean.
- © The Geological Society of London 2002
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We have some fun events planned for children at Skipton Library this February Half Term!
Monday 17th February at 10 am – 12 noon we are having a Harry Potter-themed Art Workshop. This is a FREE event, aimed at 6-12 years. Please book your place.
Tuesday 18th February at 10-11.30am we are having a Family Junk Craft session. This is a FREE event, aimed at families. Come along and create something out of junk, there will be a prize for the best one! Please book your place.
Thursday 20th February at 10.30-11.30am we are having a Graffiti Art session. This is FREE to library members or £2.50 for non-members. This is aimed at 8-12 years. Please book your place.
Friday 21st February at 10.30 am we are having a family singing session. This is a FREE event suitable for all ages.
Please contact the library on 01609 534548 to book a place on these activities, except for the singing session which is a drop-in, no need to book, just come along and join in the fun
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10th Agricultural Science Symposium: September 26th, 2019
This year's symposium on Thursday, September 26, 2019, was dedicated to the highly topical topic "Biodiversity in the agricultural landscape: measure - promote - shape".During the one-day symposium here in Weihenstephan, the significance/value of biodiversity, the causes of biodiversity loss and the effects of different practices, measures and new approaches on diversity were highlighted and discussed. One goal was to bridge the apparent differences between agriculture and society and to find a way to live together instead of against each other.
Summaries of talks and posters in german language are availabe in the proceedings
and the supplement of the proceedings.
coverage in the media:
https://www.br.de/mediathek/podcast/landwirtschaft-und-umwelt/mercosur-abkommen-landwirte-befuerchten-preisdruck/1743801 (ab Minute 19:55)


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Union Station Holiday Festivities to Include Polar Express Train Rides
St. Louis, MO/July 25, 2017 (STL.News) – St. Louis Union Station will once again be a family destination this holiday season. With Christmas exactly six-months away, Union Station officials have announced a series of special holiday events centered on the return of The Polar Express™ Train Ride to St. Louis. The last time it was here was in 2015. The 2017 celebration will include holiday fire and light shows on the train shed lake, a series of holiday dinners in the station's Grand Hall, and rides on The Polar Express train. It all begins on November 24th, the day after Thanksgiving, and runs through December 30th.
The Polar Express is the story of a boy's magical Christmas Eve train ride to the North Pole and his meeting with Santa. The Polar Express train ride will take passengers on a round-trip journey from Union Station to the "North Pole." Set to the sounds of the motion picture soundtrack, passengers will relive the magic as they read along with the classic children's book, The Polar Express by Chris Van Allsburg. Hot chocolate and cookies will be served onboard. Santa and his helpers will board the train at the North Pole and each child will be given a keepsake silver sleigh bell. Passengers will be led in singing Christmas carols on the ride back to St. Louis Union Station.
Both coach and first-class tickets are available for The Polar Express. First-class ticket holders will be seated at four-top tables and receive a commemorative mug, as well as a free picture with Santa. Hotel packages that include train tickets and a stay at the St. Louis Union Station Hotel went on sale July 25th. Train ride-only tickets will go on sale August 1, 2017 at 9:00 a.m. All tickets and packages can be purchased online at STLPolarExpressRide.com.
In conjunction with The Polar Express train, Union Station also will host a series of magical holiday dinners in the beautiful Grand Hall of the historic train station. The buffet-style dinners will include separate adult and children's selections as well as an elaborate holiday dessert selection. Dinner tickets are $25 for adults, $20 for children 12 and under. Kids two and under are free. Diners can enjoy a special 3-D light show projected on the ceiling of the Grand Hall, plus visits from Santa's elves and other festive, holiday characters. Reservations may be purchased online at www.STLPolarExpressRide.com.
Another holiday event returning to Union Station this year is the holiday fire and light show in the train shed lake. Just like last year, the multi-million-dollar fire, water, and light music show features a 100-foot long waterfall with 50 nozzles that spray water 40-feet down into the lake, and fire will shoot 25-feet into the air. The dancing lights, water and fire are set to holiday music. Shows run daily at 5:00, 6:00, 7:00, 8:00 and 9:00 p.m.
There will be no indoor holiday events at Union Station Hotel this year because of construction of the $45 million St. Louis Aquarium which gets underway this fall. The 65,000-square-foot aquarium is expected to open in Summer 2019.
Parking for all events is available in the Union Station lot at 18th and Clark. Polar Express ticket holders can park for just $5. Union Station is also accessible by MetroLink, with a stop just outside the train shed.
STL.News publisher St. Louis Media, LLC
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