The General Equilibrium Wage Impact of Trade-Induced Shifts in Industrial Compositions of Employment in Brazilian Cities, 1991-2000

Conventionally, it is presumed that restructuring of industrial composition of employment only modestly affects the average wage. This is because in a partial equilibrium setting such a restructuring affects the calculation of the average wage only through changes in employment shares of industries used as weights on constant industry wages. On the contrary, this paper brings substantial evidence indicating that aside from such partial equilibrium shift-share effects, a change in industrial composition sizably impacts all industry wages through general equilibrium (G.E.) feed-backs from the average wage – as a reservation wage in all industries in a search and bargaining framework – onto all industry wages. In particular, this paper uses Brazilian census data for years 1991 and 2000 to study the G.E. wage impacts of exogenous shifts in industrial compositions in cities of Brazil induced by substantial trade liberalization in this country during the 1990s. A restructuring of industrial composition in a city favoring high-wage industries that modestly raises the average wage in this city by only 1% through shift-share accounting, is estimated here to increase all industry wages in the city in average by at least twice as much – between 2 to 4 percent – in the long-run through the G.E impacts, resulting in an overall increase of 3 to 5 percent in the average wage. Concerns about endogeneity is address by using an IV strategy that exploits distance of a city from major international commercial ports as an indicator of how the change in trade policy impacted its industrial composition. The result is also robust to correcting for sample selection bias generated by regional migrations and to the presence of alternative explanatory mechanisms. The finding here highlights the importance of considering G.E. interactions in policy evaluations. It also indicates that major changes in national industrial or trade policies in developing countries such as Brazil, with already non-uniform distribution of economic development across regions, create geographical winners and losers depending on how the impacts are distributed across different localities sub-nationally. If the distribution of impacts is such that the losers-to-be regions are those already suffering, then balancing measures are necessary to avoid spatially uneven sub-national economic development.Industrial Composition, Wage Structure, International Trade, Sub-national Economic Development, Spatial Distribution of Policy Impacts, Brazil

CFMT: a collaborative filtering approach based on the nonnegative matrix factorization technique and trust relationships

peer reviewedAs a method of information filtering, the Recommender System (RS) has gained considerable popularity because of its efficiency and provision of the most superior numbers of useful items. A recommender system is a proposed solution to the information overload problem in social media and algorithms. Collaborative Filtering (CF) is a practical approach to the recommendation; however, it is characterized by cold start and data sparsity, the most severe barriers against providing accurate recommendations. Rating matrices are finely represented by Nonnegative Matrix Factorization (NMF) models, fundamental models in CF-based RSs. However, most NMF methods do not provide reasonable accuracy due to the dispersion of the rating matrix. As a result of the sparsity of data and problems concerning the cold start, information on the trust network among users is further utilized to elevate RS performance. Therefore, this study suggests a novel trust-based matrix factorization technique referred to as CFMT, which uses the social network data in the recommendation process by modeling user’s roles as trustees and trusters, given the trust network’s structural information. The proposed method seeks to lower the sparsity of the data and the cold start problem by integrating information sources including ratings and trust statements into the recommendation model, an attempt by which significant superiority over state-of-the-art approaches is demonstrated an empirical examination of real-world datasets

The General Equilibrium Wage Impact of Trade-Induced Shifts in Industrial Compositions of Employment in Brazilian Cities, 1991-2000

Conventionally, it is presumed that restructuring of industrial composition of employment only modestly affects the average wage. This is because in a partial equilibrium setting such a restructuring affects the calculation of the average wage only through changes in employment shares of industries used as weights on constant industry wages. On the contrary, this paper brings substantial evidence indicating that aside from such partial equilibrium shift-share effects, a change in industrial composition sizably impacts all industry wages through general equilibrium (G.E.) feed-backs from the average wage – as a reservation wage in all industries in a search and bargaining framework – onto all industry wages. In particular, this paper uses Brazilian census data for years 1991 and 2000 to study the G.E. wage impacts of exogenous shifts in industrial compositions in cities of Brazil induced by substantial trade liberalization in this country during the 1990s. A restructuring of industrial composition in a city favoring high-wage industries that modestly raises the average wage in this city by only 1% through shift-share accounting, is estimated here to increase all industry wages in the city in average by at least twice as much – between 2 to 4 percent – in the long-run through the G.E impacts, resulting in an overall increase of 3 to 5 percent in the average wage. Concerns about endogeneity is address by using an IV strategy that exploits distance of a city from major international commercial ports as an indicator of how the change in trade policy impacted its industrial composition. The result is also robust to correcting for sample selection bias generated by regional migrations and to the presence of alternative explanatory mechanisms. The finding here highlights the importance of considering G.E. interactions in policy evaluations. It also indicates that major changes in national industrial or trade policies in developing countries such as Brazil, with already non-uniform distribution of economic development across regions, create geographical winners and losers depending on how the impacts are distributed across different localities sub-nationally. If the distribution of impacts is such that the losers-to-be regions are those already suffering, then balancing measures are necessary to avoid spatially uneven sub-national economic development

Arbuscular mycorrhizal fungi (AMF) root colonization dynamics of Molinia caerulea (L.) Moench. in grasslands and post-industrial sites

This is an accepted manuscript of an article published by Elsevier in Ecological Engineering on 05/08/2016, available online: https://doi-org.ezproxy.wlv.ac.uk/10.1016/j.ecoleng.2016.06.029 The accepted version of the publication may differ from the final published version.The aims of this studies were: (i) to examine the influence of heavy metal content (Zn, Cd, Pb, Fe, Cu) and other physico-chemical soil parameters on the level of root colonization of Molinia caerulea and (ii) to relate root colonisation parameters and soil variables to Molinia caerulea abundance in two contrasting habitats (grasslands and heavy metal contaminated sites). The sites differ significantly in terms of bio-available heavy metal contents, particularly Zn (34 times more than grasslands), soil texture, CaCO3, organic matter (LOI%), Mg and nitrate content. Principal Component Analysis showed the strong negative correlations between frequency of mycorrhization (F), arbuscular abundance (A%) and intensity of root cortex colonisation (M%) and concentration of bio-available Zn and Cd. Moreover, no positive correlation between root colonization of Molinia and its abundance was found. The frequency of mycorrhization of root fragments (F%) was only slightly different between these two habitats, whereas the intensity of root cortex colonisation (M%) and relative arbuscular abundance (A%) were significantly lower (3 and 4 times respectively) on the post-industrial sites. The bioavailable Zn content in the substratum of post-industrial sites was strongly negatively correlated with species richness, Shannon diversity index and Evenness. In contrast, these relationships were not statistically significant in grasslands. Based on obtained results we could draw a model of possible relationships between root colonization of Molinia, HM content and Molinia abundance on grasslands and post-industrial sites. Bioavailable Zn content in the soil is a one of main factors influencing the Molinia community diversity. In the grasslands, lower amounts of bioavailable Zn, resulted in higher species richness (R) and species diversity (H) which in turn lead to higher root colonization. On the other hand, on the post-industrial sites, the elevated bioavailable Zn content strongly decreases the plant species richness (R) and species diversity (H) and this caused the decline in root colonization parameters. The low species richness on Zn-polluted sites allowed Molinia to reach higher abundance since the competition with other species is reduced

Labour market outcomes of shifts in industrial composition in Brazil and Mexico

Conventionally, it is believed that wages are primarily determined by aggregate demand for labour, treating its industrial composition as irrelevant. E.g., while trade liberalization affects aggregate labour demand and its industrial composition by differently impacting within-industry labour demands, it is deemed to affect wages mainly through the former rather than the latter. In principle, given that industries pay differently to similar workers, compositional shifts that favour high premium industries, increase the likelihood of high-paying employment and raise the value of outside options for unemployed workers within skill-groups. Consequently, wages strategically increase in all industries. Chapters 1 and 2 explore whether after controlling for changes in aggregate demand for labour, shifts in its industrial composition play an important role in determining wages. Guided by the outcome of a general equilibrium model, exogenous, trade-induced variation in change in composition of local employment across cities in Mexico and Brazil during the 1990s is used to identify the associated causal wage effects, while controlling for changes in local demands for labour. It is found that shifts in industrial composition of local employment substantially impacts local sectoral wages. Not much is known about the reasons behind differences in self-employment rate across space. While differences in local factors might matter, such factors are also impacted by changes in self-employment rate, making identification difficult. Chapter 3 asks to what extent local wages and wage-employment rate are important in determining local self-employment rate. Building on the structure provided by a multi-city, multi-industry search and bargaining model of a labour market, the 1991 and 2000 waves of the Brazilian household census data are used to identify the long-term, causal effects of local employment rate and wages on local self-employment rate across Brazilian sub-national labour markets. Exogenous variation in local structures of wages and employment across Brazilian cities that were induced by trade liberalization of the 1990s in Brazil are used as the basis of the identification strategy. It is found that reallocation to self-employment from unemployment causally, and inversely, depends on local average wage and employment rate, and is substantially more responsive to changes in local wages.Arts, Faculty ofVancouver School of EconomicsGraduat