The rise and fall in the price of food, fuel and manufactured goods : interdependency between prices and technology determining comparative advantages and development paths

Green innovation, which enables us to extract energy from food crops, caused a food shortage in 2008. Countries suffering severe damage started to reconsider their agricultural policy with the aim of becoming more autonomous. The food price hike of the time looks like a reversal of the celebrated Singer-Prebisch thesis proposed in the 1950s. This paper examines the consequences of this trend on the comparative advantages and development strategies of developing countries. For that purpose, first, trends and short-run fluctuations in the prices of fuel and bio-energy crops are investigated. It is shown that the price series of fuels and the crops are synchronized only after the fuel extracting technology came into effect. Second, the reversal of the Singer-Prebisch thesis is underpinned by the generic form of an endogenous growth model developed by Rebelo (1991). It is shown that as an economy grows, appreciation of the non-reproducible, such as mineral resources and raw labor, over the reproducible, such as capital goods, is the norm rather than an anomaly. Third, the consequences of the food price hike and underlying capital accumulation on the development strategies of labor-abundant and low-income countries are explored. It is concluded that the impact of the food price hikes on the alteration of a development strategy is only incremental, without reinforcement from raw-labor-saving innovation. A case study of inventions by JUKI Corporation, a world-leader in the sewing machine market exemplifies the fact that, of all the major inventions the company have made, raw-labor-saving inventions have not dominated, although JUKI's machines are sold to one of the most raw-labor-intensive industries.

How do free trade agreements change import prices? : firm-level evidence from China's imports from ASEAN

The literature has revealed the positive impacts of free trade agreements (FTAs) on export prices by employing product-level trade data. This paper empirically examines the impacts of FTAs on import prices at the firm level. We focus on firm-level imports in China from ASEAN countries by employing China’s firm-product-level trade data. As a result, controlling for firm characteristics and product characteristics, we could not find significantly positive impacts of an FTA’s entry into force on import prices of FTA eligible products. Instead, we found a significant increase in import quantities of FTA eligible products. Thus, at the firm level, the gains from FTAs for exporters may be the increase in export quantities rather than the rise in export prices.

Analysis of house prices to assess economic impacts of new public transport infrastructure: Madrid metro line 12.

Transportation infrastructure is known to affect the value of real estate property by virtue of changes in accessibility. The impact of transportation facilities is highly localized as well, and it is possible that spillover effects result from the capitalization of accessibility. The objective of this study was to review the theoretical background related to spatial hedonic models and the opportunities that they provided to evaluate the effect of new transportation infrastructure. An empirical case study is presented: the Madrid Metro Line 12, known as Metrosur, in the region of Madrid, Spain. The effect of proximity to metro stations on housing prices was evaluated. The analysis took into account a host of variables, including structure, location, and neighborhood and made use of three modeling approaches: linear regression estimation with ordinary least squares, spatial error, and spatial lag. The results indicated that better accessibility to Metrosur stations had a positive impact on real estate values and that the effect was marked in cases in which a house was for sale. The results also showed the presence of submarkets, which were well defined by geographic boundaries, and transport fares, which implied that the economic benefits differed across municipalities.

Forecasting Electricity Prices and their volatilities using Unobserved Components.

The liberalization of electricity markets more than ten years ago in the vast majority of developed countries has introduced the need of modelling and forecasting electricity prices and volatilities, both in the short and long term. Thus, there is a need of providing methodology that is able to deal with the most important features of electricity price series, which are well known for presenting not only structure in conditional mean but also time-varying conditional variances. In this work we propose a new model, which allows to extract conditionally heteroskedastic common factors from the vector of electricity prices. These common factors are jointly estimated as well as their relationship with the original vector of series, and the dynamics affecting both their conditional mean and variance. The estimation of the model is carried out under the state-space formulation. The new model proposed is applied to extract seasonal common dynamic factors as well as common volatility factors for electricity prices and the estimation results are used to forecast electricity prices and their volatilities in the Spanish zone of the Iberian Market. Several simplified/alternative models are also considered as benchmarks to illustrate that the proposed approach is superior to all of them in terms of explanatory and predictive power.

Efficiency and spatial equity impacts of high-speed rail extensions in urban areas

Urban areas benefit from significant improvements in accessibility when a new high speed rail (HSR) project is built. These improvements, which are due mainly to a rise in efficiency, produce locational advantagesand increase the attractiveness of these cities, thereby possibly enhancing their competitivenessand economic growth. However, there may be equity issues at stake, as the main accessibility benefits are primarily concentrated in urban areas with a HSR station, whereas other locations obtain only limited benefits. HSR extensions may contribute to an increase in spatial imbalance and lead to more polarized patterns of spatial development. Procedures for assessing the spatial impacts of HSR must therefore follow a twofold approach which addresses issues of both efficiency and equity. This analysis can be made by jointly assessing both the magnitude and distribution of the accessibility improvements deriving from a HSR project. This paper describes an assessment methodology for HSR projects which follows this twofold approach. The procedure uses spatial impact analysis techniques and is based on the computation of accessibility indicators, supported by a Geographical Information System (GIS). Efficiency impacts are assessed in terms of the improvements in accessibility resulting from the HSR project, with a focus on major urban areas; and spatial equity implications are derived from changes in the distribution of accessibility values among these urban agglomerations.

Equity pricing in the mining sector: evidence from NYSE and LSE

The study examines the Capital Asset Pricing Model (CAPM) for the mining sector using weekly stock returns from 27 companies traded on the New York Stock Exchange (NYSE) or on the London Stock Exchange (LSE) for the period of December 2008 to December 2010. The results support the use of the CAPM for the allocation of risk to companies. Most companies involved in precious metals (particularly gold), which have a beta value less than unity (Table 1), have been actuated as shelter values during the financial crisis. Values of R2 do not shown very explanatory power of fitted models (R2 < 70 %). Estimated coefficients beta are not sufficient to determine the expected returns on securities but the results of the tests conducted on sample data for the period analysed do not appear to clearly reject the CAPM

International for-profit investiments in microfinance institutions equity

In recent years international investors are increasing the focus on the social consequences of their investments along with its financial returns. The microfinance sector, considered as an asset class is a relatively young concept but the microfinance industry is experiencing a tremendous growth and has a high potential for the future. Today most social responsible investments in microfinance are performed through loans or fixed income structured finance vehicles. The possibilities to invest in the equity tranche of the industry are still scarce since the number of listed microfinance institutions is reduced and the private equity investments are limited and difficult to reach for the majority of investors. In this document we present a study on the characteristics of the MFIs and we try to shed some light on this subsector of the equity assets universe that may become important in the coming future. Keywords: Microfinance institutions, Micro-credits, Financial Institutions, Equity; Stock Exchange

International For-Profit Investments in Microfinance Institutions Equity

Purpose: The purpose of this document is to review the funding options for Microfinance Institutions (MFIs), define the size of the holdings of international investors in MFI equity and in particular the MFIs listed in stock exchanges, analyze the characteristics of these subset of the financial world and study the stock exchange evolution of some listed MFIs amid the financial crisis. Design/methodology/approach: Since academic literature on listed MFI equity is virtually inexistent, most of the information has been obtained from the World Bank, annual accounts of the listed MFIs, stock exchanges and from equity research documents. Findings and Originality/value: Microfinance Institutions share several common characteristics that make them a resilient business and the few MFIs that are listed in stock exchanges seem to have performed better in the financial crisis. Microfinance can be considered as one of the new frontiers of the expansion of the global banking industry. Practical implications: Presently, international for-profit investors have very few ways of investing in microfinance equity. Most of the equity of the MFI equity is funded locally or thanks to the local public sector. The stock exchange listing of the MFIs should drive MFIs towards a more professional management, more transparency and better governance. Social implications: Microfinance Institutions provide credit to microenterprises in poor countries that have no other alternative sources of external capital to expand its activity. If global investors could easily invest in the listed equity of the MFIs these institutions would expand its lending books and would improve its governance, part of the population living in poor areas or with lower income could ameliorate its standard of living. Originality/value: The number of Microfinance Institutions that are professionally run like commercial banks is still scarce and even more scarce are the MFI listed in public stock exchanges. Therefore the published literature on the characteristics and performance of the listed equity of the Microfinance Institutions is extremely reduced. But microfinance assets are rapidly growing and MFIs will need to list their equity in stock exchanges to sustain this expansion.

Modelling and forecasting fossil fuels, CO2 and electricity prices and their volatilities

In the current uncertain context that affects both the world economy and the energy sector, with the rapid increase in the prices of oil and gas and the very unstable political situation that affects some of the largest raw materials’ producers, there is a need for developing efficient and powerful quantitative tools that allow to model and forecast fossil fuel prices, CO2 emission allowances prices as well as electricity prices. This will improve decision making for all the agents involved in energy issues. Although there are papers focused on modelling fossil fuel prices, CO2 prices and electricity prices, the literature is scarce on attempts to consider all of them together. This paper focuses on both building a multivariate model for the aforementioned prices and comparing its results with those of univariate ones, in terms of prediction accuracy (univariate and multivariate models are compared for a large span of days, all in the first 4 months in 2011) as well as extracting common features in the volatilities of the prices of all these relevant magnitudes. The common features in volatility are extracted by means of a conditionally heteroskedastic dynamic factor model which allows to solve the curse of dimensionality problem that commonly arises when estimating multivariate GARCH models. Additionally, the common volatility factors obtained are useful for improving the forecasting intervals and have a nice economical interpretation. Besides, the results obtained and methodology proposed can be useful as a starting point for risk management or portfolio optimization under uncertainty in the current context of energy markets.

Mixed models for short-run forecasting of electricity prices: Application for the Spanish market

Short-run forecasting of electricity prices has become necessary for power generation unit schedule, since it is the basis of every profit maximization strategy. In this article a new and very easy method to compute accurate forecasts for electricity prices using mixed models is proposed. The main idea is to develop an efficient tool for one-step-ahead forecasting in the future, combining several prediction methods for which forecasting performance has been checked and compared for a span of several years. Also as a novelty, the 24 hourly time series has been modelled separately, instead of the complete time series of the prices. This allows one to take advantage of the homogeneity of these 24 time series. The purpose of this paper is to select the model that leads to smaller prediction errors and to obtain the appropriate length of time to use for forecasting. These results have been obtained by means of a computational experiment. A mixed model which combines the advantages of the two new models discussed is proposed. Some numerical results for the Spanish market are shown, but this new methodology can be applied to other electricity markets as well