Barriers to the investment in the Concentrated Solar Power sector in Morocco: A foresight approach using the Cross Impact Analysis for a large number of events

The Scenario Analysis methods have often been used by policy makers as an instrument to manage uncertainty and to support the shaping of long-term economy policies. In this research, we apply Scenario Analysis in order to identify the barriers affecting the decision to invest in the Concentrated Solar Power (CSP) sector in Morocco. Our results aim at facilitating the process of defining different paths in strategic political and policy actions. Using data from a survey on a panel of experts, the Cross Impact Analysis (CIA) and the Cross Impact Matrix System (SMIC) techniques are applied. The advantage of these techniques is that they allow including in the analysis the interlinkages between the events that will define the future scenarios. However, their limitation is that the number of events analyzed cannot be too high since the information collected from the experts increases exponentially according to the number of events introduced. We thus expand our analysis with a new methodological approach, combining the use of prospective and statistics techniques. This approach allows addressing the mentioned limitation and applying these techniques, initially restricted to 6 events in its common application, to a large number of events. The results show that uncertainty and informality would be key factors in promoting the arrival of companies in this sector. Additionally, regarding companies that already have a presence in Morocco’s renewable energy sector, an increase in activity would be achieved through improvements in the easing of financial and legal barriers.     

Public–private partnerships in Social Impact Bonds: facilitating competition or hindering transparency?

ABSTRACT

The use of Social Impact Bonds (SIBs), which introduces the potential for investor profit in public service provision, has been widely discussed. Some argue that SIBs might promote government transparency because outcome data collection and evaluation are part of contractual terms. On the other hand, some argue that SIBs might hinder government transparency because more contractual parties might lead to more uncertain data ownership and because the profit motive transforms information into a competitive advantage. This paper looks at SIBs in five countries, examining how transparency differed between SIB and non-SIB financed programmes at the same social service provider. On the positive side, SIBs led to more and longer collection of outcome data and the publication of evaluations. On the negative side, it was found that SIBs tend to generate significant obstacles to the release of data to academic researchers and that sponsored evaluations do not measure impacts.     

信息化对制造业升级的影响机制研究

信息化对制造业升级的影响日益深远，但其影响机制也更加复杂。通过微观、宏观双视角定性论述，借助GMM模型对中国283个城市2004-2014年的面板数据进行定量测度，探讨了信息化对制造业升级的影响机制。结果显示：信息化与制造业升级存在倒U型关系，当信息化程度未跨过风险拐点时，其对制造业升级会产生促进作用；信息化程度跨过风险拐点后，信息化对制造业升级的促进作用呈下降趋势。研究表明信息化并不总是促进制造业升级，信息化是机遇也是挑战，各地区需要因地制宜，结合自身工业化水平来发展信息化。     

Does urbanization reduce rural poverty? Evidence from Vietnam

This paper uses data from household surveys to contribute to the urbanization-poverty nexus literature by assessing the effect of urbanization on income, expenditure, and poverty in rural households in Vietnam. We find that the urbanization process stimulates the transition from farm to non-farm activities in rural areas. More specifically, urbanization tends to reduce farm income and increase wages and non-farm income in rural households. This suggests that total income and consumption expenditure of rural households are more likely to increase with urbanization. Finally, we find also that urbanization helps decrease the expenditure poverty rate of rural households, albeit by a small magnitude.     

The Indonesian macroeconomy and the yield curve: A dynamic latent factor approach

We develop a fine representation of the term structure of interest rates in Indonesia and create a link between the yield curve and macroeconomic fundamentals. We construct a state-space representation of the yield curve as a function of three time-varying parameters: level, slope, and curvature factors. The model is then expanded to include three macroeconomic variables: real activity, inflation, and interest rates. We find that the dynamic latent factor model provides a very good fit to characterise the Indonesian yield curve in terms of the statistical properties for each maturity, and in terms of the properties of three latent yield-curve factors. With regards to the relationship to the macroeconomy, we find that there is a large amount of idiosyncratic variation in the yield curve movements. Therefore, macroeconomic variables can only explain small dynamics in the yield curve.     

The forthcoming Artificial Intelligence (AI) revolution: Its impact on society and firms

The impact of the industrial and digital (information) revolutions has, undoubtedly, been substantial on practically all aspects of our society, life, firms and employment. Will the forthcoming AI revolution produce similar, far-reaching effects? By examining analogous inventions of the industrial, digital and AI revolutions, this article claims that the latter is on target and that it would bring extensive changes that will also affect all aspects of our society and life. In addition, its impact on firms and employment will be considerable, resulting in richly interconnected organizations with decision making based on the analysis and exploitation of “big” data and intensified, global competition among firms. People will be capable of buying goods and obtaining services from anywhere in the world using the Internet, and exploiting the unlimited, additional benefits that will open through the widespread usage of AI inventions. The paper concludes that significant competitive advantages will continue to accrue to those utilizing the Internet widely and willing to take entrepreneurial risks in order to turn innovative products/services into worldwide commercial success stories. The greatest challenge facing societies and firms would be utilizing the benefits of availing AI technologies, providing vast opportunities for both new products/services and immense productivity improvements while avoiding the dangers and disadvantages in terms of increased unemployment and greater wealth inequalities.     

Information,market power,and price volatility

We consider demand function competition with a finite number of agents and private information. We show that any degree of market power can arise in the unique equilibrium under an information structure that is arbitrarily close to complete information. Regardless of the number of agents and the correlation of payoff shocks, market power may be arbitrarily close to zero (the competitive outcome) or arbitrarily large (so there is no trade). By contrast, price volatility is always lower than the variance of the aggregate shock across all information structures. Alternative trading mechanisms lead to very distinct bounds as a comparison with Cournot competition establishes.     

Factor substitution and taxation in a finance constrained economy

In this paper, we examine the effects of constant-rate factor taxation on macroeconomic stability in the Woodford (1986) model. Our focus is on how the degree of factor substitution, as measured by the elasticity of factor substitution (EOS) in production, affects different balanced-budget tax rules. Analytically, we show that indeterminacy can occur under capital income taxation only when the EOS is very low, whereas indeterminacy under labor income taxation is not subject to the EOS restriction. This finding is robust when we tax all of the factor incomes with equal rates. Thus, in terms of macroeconomic stability, taxing capital income is preferred to taxing labor income.     

FDI in Sub-Saharan Africa: A longitudinal perspective on location-specific factors (2003–2010)

This paper examines the characteristics of Location Specific Factors (LSFs) in Sub-Saharan Africa (SSA) regarding inward Foreign Direct Investment (FDI) by Multinational Enterprises (MNEs). Exploratory Factor Analysis (EFA) of 758 MNEs in 2003, 1216 in 2005 and 2402 in 2010 is used to compare the variability in LSFs in ten, 15 and 19 SSA countries respectively. We find firstly the most powerful factors, influencing the political-economy and trade dynamics of hosts to FDI, stable over time. Secondly, by 2010, production inputs become the most important factor for FDI followed by political-economic stability. This result reflects findings in International Business (IB) literature. Policy implications point to unwavering need by SSA to reduce transaction costs for FDI; increase the predictability of the policy environment; and increase the productivity-adjusted cost efficiency of inputs.     

Regulators’ and stakeholders’ perspectives in a framework for bioenergy development

In this study, ten bioenergy crop rotations (corn, corn-stover, sorghum, soybean, corn-soybean, corn-soybean-canola, corn-stover-soybean, miscanthus, switchgrass, and sorghum-soybean) were selected based on local stakeholder (economically motivated) and regulator (environmentally motivated) preferences. These crops were implemented on diverse landscapes (agricultural, marginal, and agricultural plus marginal lands) one at time for 17 years using a SWAT model of the Saginaw River Watershed in Michigan. The bioenergy crops were evaluated based on 100 percent, 50 percent, and zero percent weight assigned to both stakeholders’ and regulators’ preferences using analytic hierarchy process (AHP), an optimization and decision-making technique that aims to satisfy multiple conflicting objectives. The corn-soybean-canola rotation was selected in all landscapes based on economic benefits (stakeholders’ preferences). Meanwhile, perennial grasses (miscanthus and switchgrass) were selected based on environmental benefits (regulators’ preferences), because they maintain permanent cover, require fewer inputs than traditional row crops, and are less management intensive. When implementing bioenergy crops on marginal lands, pollution generation greatly increased at the field level, indicating that these lands are likely not viable for bioenergy crop production to meet potential future renewable energy demand.