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This paper applies the decomposition method proposed by Wang et al. (2013), together with the multi-national input-output tables from World Input-Output Database (WIOD) to estimate the value-chain transition in East Asian production network. Specifically, we calculate and examine the domestic value-added absorbed abroad, foreign value-added embodied in country’s gross exports, and vertical specialization measures to explore the relative positions of major East Asian countries in the global production chain over the period of 1995-2011. The analyses are at country-aggregate, country-sector, bilateral-aggregate and bilateral-sector levels. Based on our results, we answer the important question of whether Taiwan and South Korea have used China’s production chains as an intermediary to re-export their products to other countries in the world. Furthermore, we answer the question that over the 1995-2011 periods, have Taiwan and South Korea exploited cheap labor from China to add value to their products before re-exported them to the rest of the world?

The purpose of this paper is to examine the relationship between trade integration and intra-regional business cycle synchronization using value-added trade data. Most empirical studies analyzing the relationship between trade integration and business cycle synchronization use gross trade data which suffer from double-counting. Double-counting distorts the empirical results on the estimated relationship between trade integration and business cycle synchronization. This paper explores the relationship using value-added trade data to be free from distortions caused by double-counting.

Gross trade data on exports and imports are decomposed into sub-categories following Koopman et al. (2014). Then, value-added data on exports and imports without double-counted terms are built to measure value-added bilateral trade intensity and value-added intra-industry trade intensity. Using this value-added trade intensities, the author run panel regressions for Europe and East Asian countries to examine how value-added trade intensities are correlated with output co-movements.

The paper finds that for European countries, the positive association between trade and business cycle co-movements is more evidently observed and the role of intra-industry trade increasing the business cycle synchronization is also more clearly revealed by value-added trade data. On the other hand, for East Asian countries, value-added trade data reveal that it is very uncertain whether increased trade contributes to stronger synchronization of business cycles and intra-industry trade is truly the major factor which deepens the business cycle co-movements.

First, the paper examines the relationship only by running static panel regression. There is a need to employ different methodologies such as instrumental variable regression or dynamic panel regression. Second, financial integration and policy coordination within a region are also other relevant factors which influence the intra-regional business cycle synchronization. There is a need to examine the relationship using value-added trade data with the variables measuring the degree of financial integration and policy coordination. Third, value-added trade data used in this paper has limited coverage of East Asian countries. There is also a need to extend the value-added data set to cover more countries and industries.

Most empirical literature studying the relationship between trade integration and business cycle synchronization rely on gross trade data. This paper would be the first attempt to study the relationship using value-added trade data. Duval et al. (2014) also use value-added data, but their value-added data are not supported by a solid accounting framework which decomposes a country’s gross exports into various value-added components by source and additional double-counted terms. Value-added data in this paper computed based on Koopman et al. (2014) are the total domestic value exports that are ultimately consumed abroad via final and intermediate exports. The author believes that value-added data in this paper are most relevant in estimating the relationship between trade integration and business cycle synchronization.

The purpose of this paper is to show that distinguishing between gross and net tax shields arising from interest deductions is important to firm valuation. The distinction affects the interpretation but not valuation of tax shields for the famous Miller’s (1977) model with corporate and personal taxes. However, for the well-known Miles and Ezzell’s (1985) model, the authors show that the valuation of tax shields can be materially affected. Implications to the cost of equity and optimal capital structure are discussed.

This paper proposed a simple tax shield clarification that distinguishes between gross and net tax shields. Net tax shields equal gross tax shields minus personal taxes on debt. When an after-tax riskless rate is used to discount shareholders’ tax shields, this distinction affects the interpretation but not valuation results of the Miller’s model. However, when the after-tax unlevered equity rate is used to discount tax shields under the well-known Miles and Ezzell’s (1985) model, the difference between gross and net tax shields can materially affect valuation results. According to the traditional ME model, both gross tax shields and debt interest tax payments (i.e. net tax shields) are discounted at the after-tax unlevered equity rate. By contrast, the proposed revised ME model discounts gross tax shields at the unlevered equity rate but personal taxes on debt income at the riskless rate (like debt payments). Because personal taxes on debt are nontrivial, traditional ME valuation results can noticeably differ from the revised ME model to the extent that after-tax unlevered equity and debt rates differ from one another.

For comparative purposes, the authors provide numerical examples of the traditional and revised ME models. The following constant tax rates and market discount rates are assumed: T_c=0.30, T_pb=0.20, T_ps=0.10, r=0.06, and ρ=0.10. Table I compares these two models’ valuation results. Maximum firm value for the traditional ME model is 7.89 compared to 7.00 for the revised ME model. At a 50 percent leverage ratio, equity value is reduced from 3.71 to 3.49, respectively. Importantly, the traditional ME model suggests that firm value linearly increases with leverage and implies an all-debt capital structure, whereas firm value stays relatively constant as leverage increases in the revised ME model. These capital structure differences arise due to discounting debt tax payments with the unlevered equity rate (riskless rate) in the traditional ME (revised ME) model. Figure 1 graphically summarizes these results by comparing the traditional ME model (thin lines) to the revised ME model (bold lines).

Textbook treatments of leverage gains to firms or projects with corporate and personal taxes should be amended to take into account this previously unrecognized tradeoff. Also, empirical analyses of capital structure are recommended on the sensitivity of leverage ratios to the gross-tax-gain/debt-personal taxes tradeoff.

Financial managers need to understand how to value interest tax shields on debt in making capital structure decisions, computing the cost of capital, and valuing the firm.

The valuation of interest tax shields in finance is a long-standing controversy. Nobel prize winners Modigliani and Miller (MM) wrote numerous papers on this subject and gained fame from their ideas in this area. However, application of their ideas has changed over time due to the Miles and Ezzell’s (ME) model of firm valuation. The present paper adapts the pathbreaking ideas of MM to the valuation framework of ME. Students and practitioners in finance can benefit by the valuation results in the paper.

No previous studies have recognized the valuation issues resolved in the paper on the application of the popular and contemporary ME model of firm valuation to the MM valuation concepts. The new arguments in the paper are easy to understand and readily applied to firm valuation.

The purpose of this paper is to extricate value-added exports in information and communications technology (ICT) industry earned by Taiwan and Korea. Additionally, the authors decompose Taiwan and Korea’s gross exports into various meaningful components.

The authors use the inter-country input-output (ICIO) table which endows with cost structures of industries as well as trade information, facilitating in keeping track of the flow of products and value-added. The ICIO table used in this paper comes from the World Input-Output Database. The authors also use the way Wang et al. (2013) decomposed the intermediate goods exports into various components to provide further insights.

The empirical results indicate that Taiwan and Korea’s ICT export to the world shrink by 47.8 and 40.9 percent when the trades are measured in value-added terms. Taiwan and Korea’s ICT export will also decrease by 75.1 and 57.8 percent. From the viewpoint of value added in trade, the share of value added embodied in Taiwan and Korea’s gross ICT exports continued to decrease and reached 24.9 and 42.2 percent in 2011, while the components of pure double counted terms kept growing in recent years.

With global value chains flourishing in recent years, conventional trade statistics not only fails to highlight the vertical specialization among different countries, but also distorts the measurement of a country’s competitiveness. This paper extricates value-added exports in ICT industry earned by Taiwan and Korea and bring into focus the importance of trade in value added.

The chapter analyses the international economic specialization of the Republic of Belarus based on the balance of payments and national statistics data by type of economic activity. It also demonstrates application of the customized Trade in Value Added methodology for analysis of the international economic specialization of Belarus. The methodology has been developed for the calculation of selected key figures for 2011–2016. Using of “Input–Output” tables to measure intersectoral relationships enabled assessment of the international trade not only in terms of prices of goods and services, but in terms of value added of each product. The analysis shows that the most important industries of the international economic specialization of Belarus are oil products, chemical products, food stuffs, equipment and vehicles, transport services, computer services. Domestic value added share of exports is about 60%, which corresponds to the level of such countries of Central and Eastern Europe as the Czech Republic, Slovakia, Estonia, Poland. Consequently, import intensity of exports accounts for about 40%. The results of the study have allowed to assess the interrelation between production, exports, and economic growth and to provide recommendations ensuring a deficit-free balance of payments.

The purpose of this paper is to explore whether stock selection strategies based on four fundamental quality indicators can generate superior returns compared to overall market.

The sample of stocks comprises the constituents of BSE-500 index, which is a broad based index consisting of highly liquid stocks from all 20 major industries of the Indian economy. Portfolios are constructed on the basis of quality indicator rankings of companies and the returns of these portfolios are compared with the overall market. Excess returns on quality based portfolios are also determined using OLS regressions of quality portfolio returns on market, size, value and momentum factor returns.

The results suggest that two of the four quality strategies, namely Grantham Quality indicator and Gross Profitability have generated superior returns after controlling for market returns as well as common anomalies such as size, value and momentum. Combining value strategies with quality strategies do not yield any significant gains relative to quality only strategies.

For investors looking to invest in the Indian stock market for a long term, this study provides evidence on the performance of some fundamental indicators that can help predict long run stock performance. The findings suggest that investors can distinguish between high-performing and low-performing stocks based on stock quality indicators.

This is the first such study to look into the performance of quality investing in the Indian stock market. As most quality investing studies have been focussed on developed economies, this paper provides out-of-sample evidence for quality investing in the context of an emerging market.

The last three decades have witnessed strong development of global value chains (GVCs). Also, the Polish economy developed international production links along with the systemic transformation from the beginning of the 1990s. This led to changes in Poland's participation in GVCs.

The Purpose of the Chapter: The study's primary purpose is to characterise the evolution of Poland's participation in GVCs since the mid-1990s, including its key determinants.

Several research methods were used to achieve the study's goal, including critical literature analysis, statistical data analysis and descriptive methods. To determine Poland's share in the GVCs, the method of estimating domestic and foreign added value was used, which allowed for measuring the scale of production fragmentation and related trade in value-added.

The analysis allowed us to conclude that Poland has increased its share in GVCs, mainly inside the EU. Also, the industrial structure underwent positive changes. The increasing Poland's participation in the GVCs was primarily due to the inflow of FDI-related technology, the transformation of the economic structure, institutional and geographical factors. The improvement in the conditions for the functioning of the Polish economy has been reflected in international competitiveness rankings, where such attributes as geographical location, macroeconomic performance, human capital, market size, technical infrastructure and innovativeness are indicated. On the other hand, however, the tightness of the law, the efficiency of the government and public administration remains a challenge.

The purpose of this paper is to investigate the association between gross profit percentage, abnormal market returns, revenue surprises and earnings surprises. Gross margin is relied upon by various market participants, as its predictive power is incremental and distinct from revenue and earnings signals; however, gross margin has received little researcher attention.

General regression specifications found in the prior literature are extended to assess the informational content of changes in gross margin percentage. In addition, various portfolios are created based around the nature of the signals (positive or negative), provided by each income statement metrics (revenue, gross margin and earnings). A sample of 5,582 quarterly observations of S & P 500 firms is compiled. The main regressions are exposed to three robustness tests that focus on industry sub-groupings, institutional ownership and fourth-quarter observations.

The main findings reveal that gross margin percentage changes and earnings surprises are significantly related to abnormal market returns in the short window around the earnings announcement date and persist into a wider window measured as the quarter after the earnings announcement date. The relationship between gross margin percentage changes and abnormal returns is more pronounced when positive (negative) changes in gross margin percentage are accompanied by positive (negative) revenue and earnings surprises.

This study relies upon S & P 500 firms which are all relatively large firms. Therefore, the results may not be generalizable to smaller firms. In addition, the gross margin change is measured as the quarter-over-quarter percentage change because there is no analyst expectation for gross margin.

This paper extends the prior literature by developing three testable hypotheses that investigate the linkages between abnormal market returns, gross margin and revenue and earnings surprises. This is the first known study to investigate the informational content of changes in gross margin percentage.

The purpose of this paper is to document for the first time the vertical specialization structure of the global pharmaceutical value chain.

The paper adopts Wang et al.’s (2013) gross exports decomposition method to trace foreign values in bilateral trade between major pharmaceutical producers, using the 2014 WIOT database.

The paper shows that as in other sectoral value chains, the pharmaceutical value chain is heavily regional. The paper identifies a strong European regional value chain, and a less intensive, Asian regional value chain. Korea is positioned in the middle of the Asian value chain, and is connected to the European regional value chain as a second-tier supplier.

The paper documents the vertical specialization structure of the global pharmaceutical value chain through gross exports decomposition method, making use of the World Input–Output Table Database 2014 which disaggregates pharmaceuticals in its industry classification for the first time.

This study aims to explore peer performance as the motivation behind gross profit manipulation through two different channels, namely, cost of goods sold (COGS) misclassification and revenue misclassification.

Gross profit expectation model (Poonawala and Nagar, 2019) and operating revenue expectation model (Malikov et al., 2018) are used to measure COGS and revenue misclassification, respectively. The panel data regression models are used to analyze the data for this study.

The study results show that firms engage in gross profit manipulation to meet the industry’s average gross margin, implying that peer performance is an important benchmark that firms strive to achieve through misclassification strategies. Further results exhibit that firms prefer COGS misclassification over revenue misclassification for manipulating gross profit, implying that firms choose the shifting strategy based on the relative advantage of each shifting tool.

The findings suggest that firms that just meet or slightly beat industry-average profitability levels are highly likely to engage in classification shifting (CS). Thus, investors and analysts should be careful when evaluating such firms by comparing them with other firms in the same industry.

First, this study is among earlier attempts to investigate CS motivated by peer performance. Second, this study investigates both tools of gross profit manipulation by taking a uniform sample of firms over the same period and provides compelling evidence that firms prefer one shifting tool over another depending on the relative advantage of each shifting tool.