A study on the effect of functional distribution of income on aggregate demand

In this thesis, we study the causal relationship between functional distribution of income and economic growth. In particular, we focus on some of the aspects that might alter the effect of the profit share on growth. After a brief introduction and literature review, the empirical contributions will be presented in Chapters 3,4 and 5. Chapter 3 analyses the effect of a contemporaneous decrease in the wage share among countries that are major trade partners. Falling wage share and wage moderation are a global phenomenon which are hardly opposed by governments. This is because lower wages are associated with lower export prices and, therefore, have a positive effect on net-exports. There is, however, a fallacy of composition problem: not all countries can improve their balance of payments contemporaneously. Studying the country members of the North America Free Trade Agreement, we find that the effect on export of a contemporaneous decrease in the wage share in Mexico, Canada and the United States, is negative in all countries. In other words, the competitive advantage that each country gains because of a reduction in its wage share (to which is associated a decrease in export prices), is offset by a contemporaneous increase in competitiveness in the other two countries. Moreover, we find that NAFTA is overall wage-led: the profit share has a negative effect on aggregate demand. Chapter 4 tests whether it is possible that the effect of the profit share on growth is different in the long run and in the short run. Following Blecker (2014) our hypothesis is that in the short run the growth regime is less wage-led than it is in the long run. The results of our empirical investigation support this hypothesis, at least for the United States over the period 1950-2014. The effect of wages on consumption increases more than proportionally compared to the effect of profits on consumption from the short to the long run. Moreover, consumer debt seem to have only a short-run effect on consumption indicating that in the long run, when debt has to be repaid, consumption depends more on the level of income and on how it is distributed. Regarding investment, the effect of capacity utilization is always larger than the effect of the profit share and that the difference between the two effects is higher in the long run than in the short run. This confirms the hypothesis that in the long run, unless there is an increase in demand, it is likely that firms are not going to increase investments even in the presence of high profits. In addition, the rentier share of profits – that comprises dividends and interest payments – has a long-run negative effect on investment. In the long run rentiers divert firms’ profits from investment and, therefore, it weakens the effect of profits on investment. Finally, Chapter 5 studies the possibility of structural breaks in the relationship between functional distribution of income and growth. We argue that, from the 1980s, financialization and the European exchange rate agreements weakened the positive effect of the profit share on growth in Italy. The growth regime is therefore becoming less profit-led and more wage-led. Our results confirm this hypothesis and also shed light on the concept of cooperative and conflictual regimes as defined by Bhaduri and Marglin (1990).

Query routing in cooperative semi-structured peer-to-peer information retrieval networks

Conventional web search engines are centralised in that a single entity crawls and indexes the documents selected for future retrieval, and the relevance models used to determine which documents are relevant to a given user query. As a result, these search engines suffer from several technical drawbacks such as handling scale, timeliness and reliability, in addition to ethical concerns such as commercial manipulation and information censorship. Alleviating the need to rely entirely on a single entity, Peer-to-Peer (P2P) Information Retrieval (IR) has been proposed as a solution, as it distributes the functional components of a web search engine – from crawling and indexing documents, to query processing – across the network of users (or, peers) who use the search engine. This strategy for constructing an IR system poses several efficiency and effectiveness challenges which have been identified in past work. Accordingly, this thesis makes several contributions towards advancing the state of the art in P2P-IR effectiveness by improving the query processing and relevance scoring aspects of a P2P web search. Federated search systems are a form of distributed information retrieval model that route the user’s information need, formulated as a query, to distributed resources and merge the retrieved result lists into a final list. P2P-IR networks are one form of federated search in routing queries and merging result among participating peers. The query is propagated through disseminated nodes to hit the peers that are most likely to contain relevant documents, then the retrieved result lists are merged at different points along the path from the relevant peers to the query initializer (or namely, customer). However, query routing in P2P-IR networks is considered as one of the major challenges and critical part in P2P-IR networks; as the relevant peers might be lost in low-quality peer selection while executing the query routing, and inevitably lead to less effective retrieval results. This motivates this thesis to study and propose query routing techniques to improve retrieval quality in such networks. Cluster-based semi-structured P2P-IR networks exploit the cluster hypothesis to organise the peers into similar semantic clusters where each such semantic cluster is managed by super-peers. In this thesis, I construct three semi-structured P2P-IR models and examine their retrieval effectiveness. I also leverage the cluster centroids at the super-peer level as content representations gathered from cooperative peers to propose a query routing approach called Inverted PeerCluster Index (IPI) that simulates the conventional inverted index of the centralised corpus to organise the statistics of peers’ terms. The results show a competitive retrieval quality in comparison to baseline approaches. Furthermore, I study the applicability of using the conventional Information Retrieval models as peer selection approaches where each peer can be considered as a big document of documents. The experimental evaluation shows comparative and significant results and explains that document retrieval methods are very effective for peer selection that brings back the analogy between documents and peers. Additionally, Learning to Rank (LtR) algorithms are exploited to build a learned classifier for peer ranking at the super-peer level. The experiments show significant results with state-of-the-art resource selection methods and competitive results to corresponding classification-based approaches. Finally, I propose reputation-based query routing approaches that exploit the idea of providing feedback on a specific item in the social community networks and manage it for future decision-making. The system monitors users’ behaviours when they click or download documents from the final ranked list as implicit feedback and mines the given information to build a reputation-based data structure. The data structure is used to score peers and then rank them for query routing. I conduct a set of experiments to cover various scenarios including noisy feedback information (i.e, providing positive feedback on non-relevant documents) to examine the robustness of reputation-based approaches. The empirical evaluation shows significant results in almost all measurement metrics with approximate improvement more than 56% compared to baseline approaches. Thus, based on the results, if one were to choose one technique, reputation-based approaches are clearly the natural choices which also can be deployed on any P2P network.