Spatial Autocorrelation and Verdoorn Law in the Portuguese NUTs III

This study analyses, through cross-section estimation methods, the influence of spatial effects in productivity (product per worker), at economic sectors level of the NUTs III of mainland Portugal, from 1995 to 1999 and from 2000 to 2005 (taking in count the data availability and the Portuguese and European context), considering the Verdoorn relationship. From the analyses of the data, by using Moran I statistics, it is stated that productivity is subject to a positive spatial autocorrelation (productivity of each of the regions develops in a similar manner to each of the neighbouring regions), above all in services. The total sectors of all regional economy present, also, indicators of being subject to positive autocorrelation in productivity. Bearing in mind the results of estimations, it can been that the effects of spatial spillovers, spatial lags (measuring spatial autocorrelation through the spatially lagged dependent variable) and spatial error (measuring spatial autocorrelation through the spatially lagged error terms), influence the Verdoorn relationship when it is applied to the economic sectors of Portuguese regions. The results obtained for the two periods are different, as expected, and are better in second period, because, essentially, the European and national public supports (Martinho, 2011)

Foreign trade, home linkages and the spatial transmission of economic fluctuations in Italy

During the recent global recession both the export-oriented northern Italian regions and those in the far less open South experienced a sharp decline in economic activity. One of the possible explanations is the existence of strong domestic linkages propagating foreign demand shocks from North to South. To assess the scope of the spatial transmission of global and local disturbances across Italian regions, in this paper we specify and estimate a bivariate structural spatial VAR model featuring GDP and foreign exports as endogenous variables. A standard gravity equation approach is implemented to model unobserved domestic regional trade flows, while regional sales on foreign markets are related to global trade fluctuations and local shocks to competitiveness, broken down into a national and an idiosyncratic component. In line with expectations, strong domestic linkages are uncovered on the basis of model estimation results. The latter show that even less export-oriented Italian regions, although broadly unaffected on impact, may eventually experience a sharp output decline following a fall in global trade of the size observed in the recent recession.panel VAR model, trade linkages, spatial econometrics

The causality between energy consumption and economic growth: A multi-sectoral analysis using non-stationary cointegrated panel data

The increasing attention given to global energy issues and the international policies needed to reduce greenhouse gas emissions have given a renewed stimulus to research interest in the linkages between the energy sector and economic performance at country level. In this paper, we analyse the causal relationship between economy and energy by adopting a Vector Error Correction Model for non-stationary and cointegrated panel data with a large sample of developed and developing countries and four distinct energy sectors. The results show that alternative country samples hardly affect the causality relations, particularly in a multivariate multi-sector frameworkEnergy Sector, Panel Unit Roots, Panel Cointegration, Vector Error Correction Models, Granger Causality

Reconstruction of Multidecadal Country-Aggregated Hydro Power Generation in Europe Based on a Random Forest Model

Hydro power can provide a source of dispatchable low-carbon electricity and a storage solution in a climate-dependent energy mix with high shares of wind and solar production. Therefore, understanding the effect climate has on hydro power generation is critical to ensure a stable energy supply, particularly at a continental scale. Here, we introduce a framework using climate data to model hydro power generation at the country level based on a machine learning method, the random forest model, to produce a publicly accessible hydro power dataset from 1979 to present for twelve European countries. In addition to producing a consistent European hydro power generation dataset covering the past 40 years, the specific novelty of this approach is to focus on the lagged effect of climate variability on hydro power. Specifically, multiple lagged values of temperature and precipitation are used. Overall, the model shows promising results, with the correlation values ranging between 0.85 and 0.98 for run-of-river and between 0.73 and 0.90 for reservoir-based generation. Compared to the more standard optimal lag approach the normalised mean absolute error reduces by an average of 10.23% and 5.99%, respectively. The model was also implemented over six Italian bidding zones to also test its skill at the sub-country scale. The model performance is only slightly degraded at the bidding zone level, but this also depends on the actual installed capacity, with higher capacities displaying higher performance. The framework and results presented could provide a useful reference for applications such as pan-European (continental) hydro power planning and for system adequacy and extreme events assessments

Agricultural R&D Lags from a Dual Perspective

This study examines the role of public agricultural research and development (R&D) in the process of knowledge production and productivity growth in U.S. agriculture from a new perspective. The seminal work of Griliches (1967) established the relationship between investments in R&D, the process of knowledge production, and the productivity enhancing benefits they create. In the literature on estimating knowledge production functions measures of multi-factor productivity (MFP) are regressed against measures of knowledge stocks, thereby enabling the researcher to quantify the relationship between the stream of investment expenditures and the productivity enhancing benefits they produce. A critical aspect of this research involves how to handle inter-temporal research spillovers, or in other words how to sum current and previous R&D expenditures into a measure that best represents the current stock of knowledge. This research expands on recently published work by Alston et al (2010) related to estimating the ideal lag structure for summing R&D investments, using data from the International Science and Technology Practice and Policy (InSTePP) Center at the University of Minnesota. We reproduce some of the analysis in the Alston et al (2010) research related to estimating knowledge production functions, but substitute an alternative measure of MFP in the analysis. Specifically, we re-estimate the knowledge production functions using a dual as opposed to a primal measure of productivity. The authors of this study have not seen this approach utilized in the literature, and we believe this novel approach will provide additional valuable insight on the process of knowledge production and productivity growth. Griliches and Jorgenson (1967) formalized the relationship between a dual and a primal measure of MFP. Commonly, a primal measure of MFP is defined as a measure of aggregate output divided by aggregate input. A dual measure can be defined as the ratio aggregate input to output prices. We outline the theoretical reasons why there may differences between the primal and dual measures of MFP. Furthermore, we compare the empirical measures of primal and dual MFP from the InSTePP database and identify differences in these measures over time. Many different lag structures for estimating knowledge stocks have been considered in the literature, including geometric, gamma, and trapezoidal distributions to name a few, and both the shape as well as the length of the distribution are important. The gamma distribution embodies several favorable characteristics: 1) all lag weights determined by the function are non-negative; 2) the shape implied is relatively smooth; 3) the gamma distribution is unimodal; 4) the distribution can be skewed to give more weight to more recent or more distant lags; and 5) the distribution can be characterized by only two parameters. We construct two grids of 64 gamma distributions based on a research lags of 35 and 50 years. The distributions can be represented by altering two parameters. The goal is to examine the best lag structure to represent the relationship between R&D expenditures, knowledge production, and the resulting productivity enhancing benefits. We do this by estimating knowledge production functions under the different lag specifications, and choose the specification that produces the lowest Sum-of-Squared Errors (SSE) in the regressions. The primary objective is to compare and contrast the results of the regression analysis with regards to the preferred lag structure using the dual as opposed to primal measure of MFP. Do the results from a primal and dual approach support a similar lag structure for summing R&D expenditures or do they contradict one another? The methodology of this study is well established, the results have direct significance to an important field of agricultural economics, and the potential to generate discussion and debate is high.Multi-factor Productivity, dual estimates, public R&D, lag distribution, Agricultural and Food Policy, Productivity Analysis,

ARE EXPORTS CAUSING GROWTH? EVIDENCE ON INTERNATIONAL TRADE EXPANSION IN CUBA, 1960-2004

Economic development in Cuban economy in the last 50 years has been involved in the so called socialist revolution time. In the external sector, the COMECON arrangements have determined its international specialization trade pattern and balance of payments position until 1989. When the Berlin Wall fell down, Cuban economy collapsed showing the malfunctions of the previous external regulated period. In this paper, we analyzed the role of exports as an engine of economic growth in Cuba considering essential events in its commercial policy-making in the long period from 1960 to 2004. Our results show that the export led growth (ELG) hypothesis is not an appealing phenomenon. Causality proofs on the basis of error correction and augmented level VAR modellings show the imperious necesssity to import for the Cuban development. The inclusion of imports not only evidences the weakness in the feedback and interrelation between economic growth and exports but also their expansion has been precisely causing growth in most of the considered periods.Cuba, Export-led Growth, commercial agreements effects, cointegration, causality, error correction and augmented VAR modelling

Regional variety and employment growth in Italian labour market areas: services versus manufacturing industries

This paper investigates the impact of regional sectoral diversity on regional employment growth in Italy over the period 1991-2001. Assuming that externalities may be stronger between industries selling similar products or sharing the same skills and technology (i.e. related industries), we analyze the role of different forms of sectoral variety at the Local Labour System (LLS) level. We consider variety both in terms of shared complementary competences that induce effective interactive learning and innovation, as well as a portfolio strategy to protect a region from external shocks in demand. Our results show strong evidence of a general beneficial effect of a diversified sectoral structure but suggest also the need to differentiate the analysis between manufacturing and services. In particular, overall local employment growth seems to be favoured by the presence of a higher variety of related service industries, while no role is played by related variety in manufacturing. When looking at diversity externalities between macro-aggregates, the service industry is affected by related variety in manufacturing, while no evidence of externalities is found from tertiary sectors to manufacturing

Financial Development, Financial Fragility, and Growth

This paper attempts to reconcile the apparent contradiction between two strands of the literature on the effects of financial intermediation on economic activity. On the one hand, the empirical growth literature finds a positive effect of financial depth as measured by, for instance, private domestic credit and liquid liabilities (e.g., Levine, Loayza, and Beck 2000). On the other hand, the banking and currency crisis literature finds that monetary aggregates, such as domestic credit, are among the best predictors of crises and their related economic downturns (e.g., Kaminski and Reinhart 1999). This paper starts by illustrating these opposing effects by, first, analyzing the dynamics of output growth and financial intermediation around systemic banking crises and, second, showing that the growth enhancing effects of financial depth are weaker in countries that experienced such crises. After these illustrative exercises, the paper attempts an empirical explanation of the apparently opposing effects of financial intermediation. This explanation is based on a distinction between transitory and trend effects of domestic credit aggregates on economic growth. Working with a panel of cross-country and time-series observations, the paper estimates an encompassing model of long- and short-run effects, following Pesaran, Shin, and Smith (1999)’s Pooled Mean Group Estimator. The main result of the paper is that a positive long-run relationship between financial intermediation and output growth co-exists with a, mostly, negative short-run relationship.

Acceleration feedback control of human-induced floor vibrations

Active vibration control (AVC) via a proof-mass actuator is considered to be a suitable technique for the mitigation of vibrations caused by human motions in floor structures. It has been observed that actuator dynamics strongly influence structure dynamics despite considering collocated actuator/sensor control. The well-known property of the interlacing of poles and zeros of a collocated control system is no longer accomplished. Therefore, velocity-based feedback control, which has been previously used by other researchers, might not be a good solution. This work presents a design process for a control scheme based on acceleration feedback control with a phase-lag compensator, which will generally be different from an integrator circuit. This first-order compensator is applied to the output (acceleration) in such a way that the relative stability and potential damping to be introduced are significantly increased accounting for the interaction between floor and actuator dynamics. Additionally, a high-pass filter designed to avoid stroke saturation is applied to the control signal. The AVC system designed according to this procedure has been assessed in simulation and successfully implemented in an in-service open-plan office floor. The actual vibration reductions achieved have been approximately 60% for walking tests and over 90% for a whole-day vibration monitoring. (C) 2009 Elsevier Ltd. All rights reserved

Financial Development, Financial Fragility, and Growth

This paper attempts to reconcile the apparent contradiction between two strands of the literature on the effects of financial intermediation on economic activity. On the one hand, the empirical growth literature finds a positive effect of financial depth as measured by, for instance, private domestic credit and liquid liabilities (e.g., Levine, Loayza, and Beck 2000). On the other hand, the banking and currency crisis literature finds that monetary aggregates, such as domestic credit, are among the best predictors of crises and their related economic downturns (e.g., Kaminski and Reinhart 1999). This paper starts by illustrating these opposing effects by, first, analyzing the dynamics of output growth and financial intermediation around systemic banking crises and, second, showing that the growth enhancing effects of financial depth are weaker in countries that experienced such crises. After these illustrative exercises, the paper attempts an empirical explanation of the apparently opposing effects of financial intermediation. This explanation is based on a distinction between transitory and trend effects of domestic credit aggregates on economic growth. Working with a panel of cross-country and time-series observations, the paper estimates an encompassing model of long- and short-run effects, following Pesaran, Shin, and Smith (1999)’s Pooled Mean Group Estimator. The main result of the paper is that a positive long-run relationship between financial intermediation and output growth co-exists with a, mostly, negative short-run relationship.