mento econômico mundial, criaram-se condições para uma mudança nos fl uxos de
comércio desses países. De acordo com os dados do Banco Mundial 3 , no período
compreendido entre os anos de 1995 a 2005, as exportações brasileiras aumen- taram 155%, passando de US$ 46.506 milhões para US$ 118.529 milhões. Este desempenho favorável das exportações brasileiras reverteu o resultado comercial defi citário de US$ 7.631 milhões em 1995 para um superávit na balança comercial de US$ 40.901 milhões em 2005. Quanto à China, as exportações cresceram 402% no mesmo período (de US$ 148.780 milhões em 1995 para US$ 761.953 milhões em 2005). Este resultado culminou em expressivo aumento da participação da China nas exportações mundiais, saltando de 2,88% em 1995 para 7,55% em 2005. Diante do considerável crescimento das exportações do Brasil e da China, torna-se importante verifi car se esse aumento da demanda externa possui a capa- cidade de propiciar o crescimento econômico sustentado nas referidas economias. Kaldor (1966, 1970) mostra que um rápido crescimento das exportações e da pro- dução de produtos de média e alta tecnologias, de alta elasticidade-renda, capazes é capaz de fomentar um círculo virtuoso de crescimento no qual a expansão do pro- duto gera expansão da produtividade (devido aos ganhos de escala) e esta, ao tornar o setor exportador mais competitivo, possibilita sua expansão. De acordo com o autor, a especialização da exportação em produtos baseados em recursos naturais não levaria ao desenvolvimento econômico por não se tratarem de bens intensivos em tecnologia e possuírem baixa elasticidade-renda e poucos encadeamentos intra e intersetoriais (Mccombie e Thirlwall, 1994). Em resumo, para Kaldor (1966, 1970), o conteúdo tecnológico dos bens presentes nas pautas de exportação e importação é fundamental para a viabilização do crescimento econômico sustentado.
There is no strong evidence of exchange rate volatility on real export could be due to the exchange rate policy and its management implemented in Malaysia are satisfactory to avoid the adverse impact of exchange rate volatility on export. Malaysia adopts a managed floating exchange rate. In the long run, exporters of manufactured goods in Malaysia shall continue to improve their products through innovation and high technology. Technological improvement, innovation and knowledge driven activities in manufacturing sectors are crucial to remain competitive in exports. Innovation means breach into new markets, improve market share and increase returns. Innovation would lead to higher returns to workers. The pivotal is to expand innovation capabilities and to create continuous innovation. Disruptive innovations create new markets, which will replace existing markets and displace earlier technologies. Both continuous and disruptive innovations are important to increase productivity and move up the value chain to sustain economic growth in the long run (MOF, 2013). An effective marketing approach shall be adopted to promote exports of Malaysia. Exports shall be further diversified with more focused on intra-regional trade in Association of Southeast Asian Nations Economic Community (AEC), which was launched in 2010 with the aims to promote free flow of goods, services, investment, capital and skilled labour to attract investment and trade in the region. AEC would provide export market as well as challenge to exports of Malaysian manufactured goods in the region. The AEC region has a large population and its GDP per capita is increasing. The successful of AEC will support the national transformation programme of Malaysia is to foster its agenda to be a high income nation by 2020 (MOF, 2013).
An important strand of Robert Basmann’s early work was devoted to the estimation of simultaneous equations (see Basmann, 1957, 1959, 1961, or 1963, to mention a few). Ex- amples of simultaneous systems of equations in economics are the study of the domestic and foreign demand of outputs across ﬁrms, of the consumption of diﬀerent goods and services across households, or the behavior of diﬀerent workers within ﬁrms or sectors. A host of economic problems at various levels of aggregation involves panel data and systems of equations. Two econometric problems which complicate the analysis con- siderably are the following: The data broadly speaking may be missing in the sense of censoring or truncation and is most likely cross-sectionally dependent (e.g., see Pinkse and Slade, 1998; McMillen, 2002; Smith and LeSage, 2004; Pinkse, Slade, and Shen, 2006; Klier and McMillen, 2008; Smirnov, 2010; Conley and Topa, 2007; Case, 1992; Wang, Iglesias, and Wooldridge, 2013; for approaches towards estimating problems with cross-sectionally dependent binary outcome variables; or LeSage, 2000; Flores-Lagunes and Schnier, 2012; Xu and Lee, 2015a; Xu and Lee, 2015b; LeSage and Pace, 2009; for cross-section approaches towards a wider range of models with cross-sectionally depen- dent, censored or truncated and other limited dependent variables). While the literature on spatial and social-interaction models has formulated and analyzed models for systems of equations (see, e.g., Cohen and Morrison Paul, 2004, 2007; Kelejian and Prucha, 2004; Wang, Li, and Wang, 2014; Baltagi and Deng, 2015; Wang, Lee, and Bao, 2015), in these approaches the structural form of the model is linear in parameters, and, except for Co- hen and Morrison Paul (2004) and Baltagi and Deng (2015), the approaches are designed for an analysis of cross sections of units.
There are a number of empirical studies on firm locations in CIB. Head and Ries (1996) find that in post-liberalization China, foreign firms located in cities where other foreign firms had located earlier, after controlling for fiscal incentives and infrastructure, highlighting the importance of agglomeration economies. Sridhar (2005), based on an anecdotal survey of India’s firms, argues that infrastructure is an important determinant of firm location in the growth centres of India. Without the infrastructure (power, telecom, roads and banking), many firms (even some representing local entrepreneurship) would not have located there. This is consistent with Rajaraman et al. (1999) who reported that abundant power was an important factor attracting investment into a major Indian state during the eighties. According to Mani et al. (1996), power availability (rather than its price), reliable infrastructure and factors of production played a significant role in firm location decisions across major Indian states. Tulasidhar and Rao’s (1986) analysis of a large number of medium- and large-scale industries in an Indian state indicated that the sales tax incentive, whichever way designed, was not the appropriate instrument to raise the level of investment or spread this to backward areas.
I also examine the behavior of Chinese exporters during the crisis by breaking down export growth into the intensive and extensive margins, as presented in section IV. In this part of exercise, we established two results: (1) variation in trade across time is dominated by the intensive margin and (2) recent crisis appears to have compelled producers to rush from the ordinary trade markets toward processing trade markets. Analysis of the extensive and intensive margins increases understanding of trade patterns and the relative efficiency with which economies allocate resources. A large and growing body of theoretical and empirical work in international trade suggests that trade liberalization raises aggregate productivity via the extensive margin: as trade costs fall, the least productive firms exit, while the most productive firms expand, and, within surviving firms, the least productive products are dropped -. I also show that the role of the intensive margin in total export growth increases substantially during the crisis. In particular, the intensive margin among FIEs and processing trade are more influential in explaining variation in trade during the financial crisis than the extensive margin. This large (negative) growth rate in the intensive margin is also supportive of predictions consistent with traditional theories advocating an important role for terms of trade effects .
In this paper, we match two separate Chinese micro-level data sets to get the sample we are employing in the econometric analysis. The first data set is the Annual Survey of Industrial Production (ASIP) spanning the period 1998-2007. This survey, which collects annual firm-level data, is conducted by Chinese Na- tional Bureau of Statistics (NBSC). The data set is quite inclusive, in the sense that it incorporates all Chinese State-owned Enterprises (SOEs henceforth) and non-SOEs with annual sales over 5 million yuan (roughly speaking, 650,000 dollars at that time). In the survey, detailed firm-level information was collected, such as firms’ geographic location, year of operation (i.e. the age of the firm), ownership type (state-owned, collective, private, foreign, etc.), employment, production and sales, balance sheet variables, and tax. As for this research, we focus on sales (especially exporting sales values) and balance sheet information, from which we construct exporting and finance variables in the econometric exercise. The second data set we use is product-level data from Chinese Customs (GACC), which were collected at a monthly frequency over the period 2000-2006. We add up values belonging to the same exporting entity over 12 months to obtain firm-level annual data, and thus, we can match it with the industrial survey data set. The Customs data cover the universe of transactions going through Chinese Customs, and con- tain firm-level information like geographic location, ownership type, exporting and importing variables (values, quantities, and unit prices), type of trade, mode of shipment, transit country, export destination country, and import source country.
international trade has been considered as an advent of rapid economic growth. Industrial manufacturing export in China, India and Brazil is on the rise, therefore the manufactured products which are exported to different parts of the world requires higher energy consumption. Suri and Chapman (1998) discussed that Industrial manufacturing export for all developing countries is rising. They also concluded that, the growth rate in this section is higher for developing countries. The other interesting aspect to this argument is that the demand for these products from these economies is increasing at a faster rate and the clients being the developed economies. This is because of the availability of these products at a much cheaper rate because of the low cost resources in developing economies, especially in China, India and Brazil. In this paper Industrial exports share in total exports is used as a proxy for industrial export.
Real/US dollar exchange rate; the overnight market interest rate (Selic). These varia- bles are denoted by output, inflation, erate and interest, and were log-transformed to facilitate interpretation. Exception is made to the interest rate, which is measured in percentage points. The inflation rate was negative for September of 1995 (-1.08 per- cent). In order to apply the log operator, a constant c= 1.1 was added to the inflation rate over the whole period. This procedure is usual and does not affect the coefficients of interest as the added constant simply alters the intercept of the inflation regression equation. Data for the robustness analysis include an index for world exports, the U.S. Prime rate, a consumer price index (IPCA), an index for industrial production; the internal debt/GDP ratio, a commodity price index and the price for crude oil. The details for the series used are presented in the appendix.
From the point of view of developing countries, the hypothesis that globalization has caused an increase in specialization according to comparative advantage should lead to an eﬀect that is opposite to that observed in industrialized countries. Indeed, according to traditional trade theory, in developing countries a greater participation in international markets should be asso- ciated with the exploitation of comparative advantage in goods that are intensive in unskilled labor. This should cause a shift in demand towards this type of workers, and lead to a reduction in the wage diﬀerential with respect to their skilled counterparts. However, in the context of the second hypothesis highlighted above, the same international economic activities that are often associated with the exploitation of comparative advantage — the use of imported inputs, exports and FDI — could also act as channels for the international diﬀusion of skill-biased technologies developed in industrialized countries, which in principle could diminish or even compensate for the shifts in labor demand caused by increased specialization. Thus, while in industrialized countries the labor demand eﬀects of greater international integration and those of skill-biased 1 See Wood (1994).
The dependent variable is faculty research productivity, which is also continuous, measured in terms of the total number of articles published in an academic book or journal. Although various techniques were used to measure faculty research publication productivity in research studies (Bornmann & Daniel, 2009; Braxton & Bayer, 1986; Hirsch, 2005, 2007), this study attempted to measure faculty research productivity by simply counting the number of scholarly articles published in a given three-year period because of its greater applicability to different environments, disciplines, and country contexts. Furthermore, the preliminary analysis confirmed that scholarly articles are the most preferred publication produced by both Brazilian and Chinese faculty members as it covers both articles published in an academic book or journal. Also, Cummings (2014) revealed that article focus are the broadest pattern explored in 19 participating countries. As a result, this measurement method is evident and widely used in the relevant literature (Fairweather, 2002; Lee & Bozeman, 2005; Shin, Jung, et al., 2014; Xian, 2015).
Two important features of that characterize how firms borrow against collateral in China also determine how we construct firm-level instrumental variables for credit rationing. The first feature is the wide acceptance of housing as collateral in firms’ borrowing, and the second one is the advocacy of pledging accounts receivable as collateral by the central government. Existing theoretical studies (e.g. Barro, 1976; Stiglitz and Weiss, 1981; Hart and Moore, 1994) have long recognized the role of collateral in enhancing firms’ financial capacity when there exists incom- plete contracting. Though empirical studies lag behind theoretical analysis, recent work by Gan (2007) and Chaney et al. (2012) provide supporting evidence for the economic significance of the collateral channel in affecting firms’ financing capacity and hence investment. In this study, we relate firms’ holding of collateral to credit rationing because the degree of credit rationing received by firms can be largely predicted by their ability to borrow against collateral.
As mentioned earlier, the trade sector is continuously playing an important role in the Bangladesh economy. In 1999, compared to 1988, Bangladesh’s total trade, total exports and total imports increased by 168%, 204% and 153% respectively. In the case of trade with our sample countries, this increase is the highest for the SAARC countries 439% (exports + imports). When separated, the increase of imports is the highest for the SAARC countries (602%), followed by ASEAN (276%) and EEC (107%); the increase of exports is the highest for the EEC countries (363%) followed by the NAFTA countries (323%), the Middle East countries (85%) and the SAARC countries (33%). Individually, in 1999, 20% of Bangladesh’s trade of our sample total occurred with the USA followed by India (12%), UK, Singapore, Japan (7%), and China, Germany (6%). In the same year the exports figures of Bangladesh are, of our sample total, 39% to the USA, 12% to Germany, 10% to UK, 7% to France, 5% to the Netherlands and Italy, 2% to Japan, Hong Kong, Spain and Canada and 1% to India and Pakistan. On the other hand, the imports figure of Bangladesh, of our sample total, is the highest from India (18%) followed by Singapore (12%), Japan (10%), China (9%) and USA and Hong Kong 8%. The over all trade balance of Bangladesh, of course, gives us disappointing results. Compared to 1988, the total trade deficit of Bangladesh increased by 115% in 1999. This figure is 987% with the SAARC countries, 1098% with India and 108% with Pakistan (IMF: Direction of Trade Statistics Yearbook, various years).
Parantap Basu et.al, (July 2003) 42 in this article explored the Panel co integration technique allows for co integrating vectors of differing magnitudes between countries, as well as country and time fixed effects. There is a long-run steady-state relationship between FDI and GDP for a cross-section of countries after allowing for country-specific effects. Permanent foreign capital does not reach closed economies until after the countries have exhibited growth, showing that trade and financial restrictions do indeed impede the inflow of foreign funds. The full panel shows bidirectional causality, the only evidence of long-run causality from FDI to GDP is in open economies.
The next section explains the data that has been used in the article and the choice of countries and time period. The section ‘South Africa and China’s market share in major export markets’ sets out the market shares of South Africa and China in the imports of each market and the way in which these have changed over time. Various indicators are presented in the section ‘Do Chinese products compete with South African exports? ’ to show the extent to which China and South Africa compete with each other at the 6-digit level of the Harmonised System (HS) classi ﬁcation. This is followed by a Constant Market Share (CMS) analysis of South African exports that identi ﬁes the degree to which changes in overall market share are attributable to changes in market share at the product level as opposed to the product composition of South African exports. The section ‘The displacement of South African exports by China’ extends the CMS analysis to calculate the extent to which changes in the overall competitiveness of South African exports are attributable to changes in competitiveness vis-à-vis China. In the section ‘Impacts by technology level and products ’, the overall picture with regard to the effects of Chinese competition is further disaggregated by technology level and products. Finally a brief comparison is drawn with the experience of Brazil, which in many ways faces similar problems from Chinese competition to those of South Africa.
Latin American economies have been hit since the global crisis in 2008 by a negative trade shock, falling commodity prices, an increase in currency valuations, and a decline in foreign direct investment inflows. Strong growth in exports to China stood as a bright spot, at least until 2015. By that year, Argentina was suffering double-digit inflation while Brazil’s growth forecast was barely positive, down from 7.5% in 2010. In Chile, investor confidence was shaken by reform of the corporate tax system. Peru had experienced reduced export revenues due to falling commodity prices that led to a contraction in mining output. Venezuela ended 2014 with an inflation rate of 64% accompanied by shortages in food and medicine. Mexico overhauled its energy and telecommunications sectors in 2014, ending the year with better prospects than in the previous year when it grew by just 1.1%. By these standards, Colombia was faring relatively well with growth prospects above 4%.
The last set of regressions needed to construct the counterfactual is for the impact of Chinese growth on Chinese imports. Once more we base our estimates on the gravity model framework (where the volume of Chinese imports depends on GDP and GDP per capita in China and the exporting country). One problem with applying the gravity model in this context is that the distance variable – calculated here as the distance between country geographic centers – enters insignificantly or with the wrong (positive) sign. A little reflection reveals why: distance from other Asian countries to China’s geographic center is not a meaningful measure of economic distance, given that much of the country’s trade-relevant economic activity is concentrated not at its center but along the coast. Bangladesh is 11 per cent closer than Vietnam to China’s center, but Vietnam is much closer to the Pearl River Delta, where much of China’s export-relevant economic activity takes place. Differences in the distance between China’s geographic center and, say, Bangkok versus Copenhagen do in fact tell us something about the relative
To see how export supply capacities have evolved over time, Figures 3a-3c plot the year- on-year change in country-sector export dummies for each of the 10 developing countries against those for China, weighted by each country’s sectoral trade shares. Immediately apparent is that the range of growth in China’s export-supply capacities is large relative to that of any other developing country. Changes in China’s export dummies take on a wide range of values, while none of the 10 countries shows nearly as much variation. As a consequence, the correlation between changes in sectoral export dummies between each country and China is weaker than the correlation in levels. The strongest correlations in changes are for Romania (0.50) and Malaysia (0.47); followed by Thailand (0.32), Sri Lanka (0.31), Hungary (0.30), the Philippines (0.30), Poland (0.22), and Turkey (0.21); and then by Pakistan (0.16) and Mexico (0.14).
We have to admit that the development path adopted by China has been a huge success in terms of economy, yet environmentally it is not as good as it looks. The negative sign in front of GDP growth rate warns policy makers that seeking a more efficient and environmentally friendly way of development is necessary. Also the statistical significance of the variables trend in both general model and regional models suggest further studies on the problem of pollution in China is needed. One possible way is to break down the GDP components and examine them individually at the regional level, and then to study the relationship between the environment and each component of GDP growth. The other direction is, as I mentioned above, to examine the impacts of different development stages on the environment in each of the 31 provinces. Both ways may have some interesting stories. Besides, gaining more data for each province will also help unveil the true story of pollution in China.
We have launched a research project trying to understand better the determinants of entrepreneurship using surveys of individuals that are being conducted in five large developing and transition countries: Russia, Brazil, China, India, and Nigeria. The samples include both entrepreneurs and non-entrepreneurs in order to understand how these groups differ in terms of three broad sets of variables put forward in social sciences as factors that potentially affect entrepreneurship: 1) individual characteristics such as skills, education, intellectual and personality traits, 2) sociological variables such as family background, social origins, social networks, values and beliefs, and 3) perceptions of the institutional, social and economic environment businesses face. While recent economic research has much emphasized the role of credit institutions (Banerjee and Newman, 1993) or of institutions securing property rights (Johnson et al., 2002; Besley, 1995; Che and Qian, 1998; Djankov et al., 2002, Frye and Zhuravskaya, 2000; Roland and Verdier, 2003), we want to take a more comprehensive approach and try to disentangle the role all these factors play in promoting entrepreneurship across a variety of settings.
Table 5 presents the impact of loss of market share to China on the exports of manufactured goods to the US for the 18 Latin American countries. As might be expected, the impact on manufactures is even more severe than on total exports. Again the overall impact was relatively small between 1996 and 2001, but increased markedly to 13 per cent in 2001-2006 with almost half of that impact being felt in the past two years. Some countries lost over 15 per cent of their manufactured exports in the five years from 2001 to 2006, and three countries lost over 10 per cent in just two years from 2004 to 2006. Andean countries such as Chile, Colombia, Ecuador and Venezuela, who have not suffered much in overall terms, saw a significant loss of market share in manufactures to China. Thus while they are protected from serious losses in their overall export earnings by their specialization in minerals and oil, they may find it more difficult to diversity into exports of manufactured goods as a result of Chinese competition.