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The crop sector in Malawi faces a number of constraints which must be overcome before agriculture can reach its full potential. This paper uses the policy analysis matrix (PAM) to assess efficiency in the crop sector and financial analysis to explore the potential of investing in a fruit juice extraction plant in Malawi. The PAM revealed that farmers in Malawi are efficient producers but they face negative incentives in the production and marketing of their products. The nominal protection coefficients (NPCs) for both maize and beans were less than 1 while those of inputs were more than 1. Similarly, the effective protection coefficients (EPCs) were less than 1, implying that the combined effect of transfers and tradable inputs is reducing the private profitability of the systems. On the other hand, the financial analysis demonstrated that Malawi can sustain a fruit juice extraction plant. The project had a positive net present value and a benefit/cost ratio greater than 1 (1.16). Recommendations made from the study relate to the need for diversification into fruits that can sustain a fruit juice extraction plant, encouraging private sector participation and reducing disincentives to crop production.

The aim of this chapter is to develop a strong research base for the academia and the industry to understand the importance of data analytics in International Trade. This chapter focuses on the case of cotton trade from India and explores different methodologies developed by the World Bank and International Trade Center to analyze the Big Data available on export and import. Through Big Data analysis, this chapter attempts to find out the export performance, market demand, export potential, and attractive markets for Indian cotton. This chapter also explores the trade competitiveness of Indian cotton over the years. The data through appropriate analysis can address some simple yet complicated questions in trade like what export potential the commodity holds, if the commodity is competitive or not in international market, what are new markets to look up to, and other similar questions. In other words, this information could make huge difference in decision-making of traders and policymakers directly, and farmers indirectly.

The purpose of this paper is to present an economic evaluation of Uruguay’s beef industry competitiveness to quantify the effects of public policies (taxes, subsidies, social charges) on the various links constituting the beef export chain and estimate the impact of transfers of resources between the beef industry and other sectors of the economy.

The Policy Analysis Matrix (PAM) techniques were employed to quantify the effects of public policies on the competitiveness of Uruguay’s beef industry. A series of PAM coefficients were calculated to assess the competitiveness of the beef export chain in 2010 and 2013 with comparison between the two years to make policy recommendations.

Beef sector returns captured by private agents decreased from 30 percent in 2010 to 10 percent in 2013. Competitiveness of the beef export chain deteriorated between 2010 and 2013 due primarily to higher prices paid for live cattle by the beef slaughtering, manufacturing, and packing sector. Uruguay’s beef industry transfers resources to the larger economy via social security payments and is penalized as a result of high capital costs.

Although three different sources of resource transfers were identified, more effort is needed to improve the precision of estimations.

The competitiveness of export chains is critical to the economic and social wellbeing of small-economy countries. They must be efficient producing for the international markets at the time they constitute pillars of the whole economy.

This study explores how to develop high-tech industries in Hunan province and enhance regional competitiveness. Through the comprehensive quantitative analysis of the development status of the high-tech industry in Hunan province, this paper provides a reference for the development of the high-tech industry in China and the world.

This study constructs a comprehensive evaluation index system of regional competitiveness in Hunan province from the five dimensions of innovation, coordination, green, openness and sharing of the “new development concept.” Through the screening and analysis of relevant economic indicators in Hunan province from 2011 to 2020, the principal component analysis method is used to measure the five development dimensions, verify the hypotheses in the study and finally draw the conclusion.

Hunan's high-tech industry is positively correlated with Hunan's regional innovation development competitiveness, regional coordinated development competitiveness, regional green development competitiveness, regional open development competitiveness and regional shared development competitiveness. Among them, the promotion effect on innovation development is the best, followed by the promotion effect on green development, coordinated development and shared development dimension. In contrast, the promotion effect on the open development dimension is relatively weak.

The statistical data selected in this study have certain timeliness. At the same time, the current economic environment is affected by the new corona pneumonia epidemic, showing specific particularity. In this context, it is bound to cause changes in the impact of high-tech industries on regional competitiveness. In addition, this paper studies the regional competitiveness of Hunan's high-tech industry from a macro perspective. Although relevant studies are conducted from five dimensions, there is a lack of micro-level research.

From five aspects of the new development concept, this study provides suggestions for developing high-tech industries in Hunan province and even China and the path to enhance regional competitiveness.

Up to now, no article measures regional competitiveness with the five development dimensions of new development: innovation, coordination, green, openness and sharing, and quantitatively analyses regional competitiveness on this basis.

The authors point out that the existing research confuses the operational liabilities formed based on the “transaction” relationship with the financial liabilities formed based on the “investment” relationship, which not only exaggerates the value of leverage but also underestimates the level of protection that companies provide for creditors alone. That is, the confusion of concepts not only triggers the problem of leverage misestimate but also triggers the short-term financial risk misestimate. The performance of “nominal leverage” and “nominal short-term solvency” based on total assets calculation cannot reflect the real leverage level and the real short-term financial risk of enterprises.

To distinguish the concepts of “assets” and “capital” and rationalize the relationship between “transactions” and “investments”, authors systematically design the “real leverage” indicators and “real short-term solvency” indicators, and measure the degree of misestimate of leverage and short-term financial risk indicators by traditional research. On this basis, this paper describes and analyses the trends of leveraged misestimate and short-term financial risk misestimate of listed companies in China and analyses which companies have more serious leverage misestimate. And it helps readers to form an objective understanding of the leveraged misestimate and short-term financial risk misestimate of listed companies in China.

Firstly, the overall high level of leverage of listed companies in China in the traditional sense is largely because of the misestimate of indicators. And this kind of misestimate is more serious among firms that have advantages in trading, such as state-owned enterprises and firms with higher market shares. Secondly, for most firms with normal solvency, traditional research systematically overestimated the negative impact of “nominal leverage” on financial risk indicators (represented by short-term solvency). The overestimation is significant in firms with serious leverage misestimate. Thirdly, indicators’ misestimate of the traditional research makes the banks cannot make effective credit decisions according to the firm's “real leverage” and “real short-term solvency”.

Firstly, clarify the differences between the concepts of “assets” and “capital”, and clarify the level of “real leverage” of listed companies in China, which is conducive to the process of “de-leveraging”. Secondly, revise the problem of misestimate of related indicators, so that financial institutions can clearly identify the true profitability and real risk level of the entity domain, and thus improve the effectiveness of credit decisions.

This paper estimates the Effective Rate of Protection (E.R.P.) for Costa Rica, the first time such an estimate has been provided for any Central American Republic. It also employs a new method for calculating each E.R.P. which, it is argued, offers at least a partial solution to the problem of tariff redundancy. The main conclusions are as follows:—

The purpose of this paper is to improve the measurement of nominal level and actual strength of China's intellectual property protection (IPP), and examine whether the increase of actual protection strength (APS) is positive or negative impact on China's provincial economic growth.

A modified approach, based on Ginarte‐Park's (GP's) and HL's approaches, is used to measure nominal level and APS of China's intellectual property rights (IPR) from 1995 to 2007. The pooled EGLS method (cross‐section fixed effect) is used to estimate the effect of China's IPP and other variables on provincial economic growth.

The paper proves that China's APS appears an increase with a phase. China's IPP level by GP approach is on the high side, whereas China's IPP level by HL approach is slightly on the low side. Nominal level of China's IPP is largely influenced by the legislation level, whereas APS mostly embodies the effect of implementing law level. The increase of China's APS has significant positive impact on provincial economic growth. However, at the outset of building an independent innovation country, too strong IPP is bad for the development of innovation capability, and bad for provincial economic growth.

Because the APS is unknown, it is impossible to use APS as the dependent variable to estimate the weights of the main influencing factors. The method that the paper assumes three main factors the same weights is second best choice. Thus, several different weights are supplemented to measure the distribution values of China's APS.

China's APS quantified by a modified approach and strong evidences can be used to estimate the effect on economic growth. Policy effectiveness could be maximized at seeking the endogenous benefit balance between strengthening IPP and promoting economic development.

The paper proposes a modified approach to measure the APS of China's IPR, and proves that the reinforcement of China's APS is beneficial to promoting provincial economic growth. However, at the outset, too strong IPP is harmful.

This article examines the impact of the US Offshore Assembly Provisions (OAP) on the effective tariff rates of the United States. The effects of OAP are incorporated theoretically into the effective rate calculation and the resulting algorithm is then applied to the 245 affected categories in 1974. The results indicate that, with the presence of OAP, ordinary effective rate calculations overstate the protection afforded to value added in US industries. Although the OAP effect was small, greater usage of the available concessions by importers could alter considerably the level and relative industry impact of the US tariff.

This work aims to study the break-even inflation rates (BEIRs), a widely used market-based measure of expected inflation. The authors focus on Italian Government bonds, one of the most liquid debt markets in the euro area.

The authors set up an auto-regressive distributed lag model and regress the BEIR on a set of variables that proxy inflation, market risk aversion, protection against deflation, credit as well as liquidity risk to get some insights into the importance of these factors. Subsequently, to disentangle market participants’ inflation expectations from their associated risk premia, the authors estimate a term structure model for the joint pricing of the Italian Government’s nominal and real yield curves, considering also a credit and a liquidity pricing factor.

The results show that BEIRs could be a misleading measure of the expected inflation due to the importance of the inflation risk premium and the credit risk effect. According to the estimates, the decrease of market-based measures of inflation observed in the last part of the sample period seems to reflect a lowering of both inflation expectations and risk premia. Inflation premia co-move with a measure of the tail risk of the long-term inflation distribution, signalling that investors become more concerned with downside risks.

This study complements the existing literature primarily based on the USA and euro area data focusing on the Italian market. To this end, the authors modify and adapt a well-known term structure model developed for nominal and real curves.