Can the HOS model explain changes in labor shares? A tale of trade and wage rigidities

This paper questions the ability of the standard HOS model to explain changes in the labor shares (LS) of income in OECD countries. We use the Davis (1998) model where there is a wage rigidity in a sub-group of countries. We show that trade openness with developing countries reduces LS in rigid-wage countries, and does not affect LS in free-wage countries. This pattern is induced by factor reallocation towards capital-intensive sectors in rigid-wage countries. Using the KLEMS dataset for 8 OECD countries over the period 1970-2005, we show that the weight of capital-intensive sectors substantially increased in Continental European countries, while it did not change or even decreased in the US and the UK. Fixed effects regressions suggest that trade intensity with China explains between 30% (IV estimates) and 60% (OLS estimates) of the observed differential labor share change between Continental Europe and Anglo-Saxon countries.Davis model; factor reallocation; elasticity of substitution; unemployment

FDI and the labor share in developing countries: A theory and some evidence

We address the effects of FDI on the labor share in developing countries. Our theory relies on the impacts of FDI on productive heterogeneity in a frictional labor market. FDI have two opposite effects: a negative force originated by technological advance, and a positive force due to increased labor market competition between …firms. We test this theory on aggregate panel data through …fixed effects and system-GMM estimations. We …find a U-shaped relationship between the labor share in the manufacturing sector and the ratio of FDI stock to GDP. Most countries are stuck in the decreasing part of the curve. --FDI,Matching frictions,Firm heterogeneity,Technological advance

Which factor bears the cost of currency crises?

This paper identifies which of the two factors, namely labour and capital, bears the cost of currency crises and for what reasons. It analyzes two main types of effects that currency crises may have on the labour share: across sector effects and within sector effects. We build a descriptive model with a tradable sector and a non-tradable one which can differ in their capital intensities so that structural changes occurring during currency crises may change the aggregate level of the labour share. The model also highlights that crises erode the bargaining power of workers so that within sectors, crises lower the labour share. We perform estimations on manufacturing sectoral panel data for 20 countries which have experienced currency crises. We conclude that currency crises lower the aggregate manufacturing labour share by 2 points on average and that this decline reflects mostly changes within sectors.Currency crisis ; Labour share ; Factor reallocation ; Matching frictions

FDI and the labor share in developing countries: A theory andsome evidence

This paper addresses the impact of FDI on the factor distribution of income in developing countries. We propose a theory that relies on the impacts of FDI on productive heterogeneity between firms in a frictional labor market. We argue that FDI have two opposite effects on the labor share: a negative force originated by market power and technological advance, and a positive force due to increased labor market competition between firms. Then, we test this theory on aggregate panel data through fixed effects and system-GMM estimations. We find a quantitatively meaningful U-shaped relationship between the labor share in the manufacturing sector and the ratio of FDI stock to GDP. However, most of the countries are stuck in the decreasing part of the curve,which we relate to multinationals' location choices.FDI; Matching frictions; Firm heterogeneity; Technological advance

FDI and the labor share in developing countries: a theory and some evidence

This paper addresses the impact of FDI on the labor share of income in developing countries. We propose a theory that relies on the impacts of FDI on productive heterogeneity between firms in a frictional labor market. We argue that FDI have two opposite effects on the labor share: a negative force originated by market power and technological advance, and a positive force due to increased labor market competition between firms. Then, we test this theory on aggregate panel data through fixed effects and system-GMM estimations. We find a quantitatively meaningful U- shaped relationship between the labor share in the manufacturing sector and the ratio of FDI stock to GDP. However, most of the countries are stuck in the decreasing part of the curve, which we relate to multinationals' location choices.FDI; Matching frictions; Firm heterogeneity; Technological advance

Experience in using a typed functional language for the development of a security application

In this paper we present our experience in developing a security application using a typed functional language. We describe how the formal grounding of its semantic and compiler have allowed for a trustworthy development and have facilitated the fulfillment of the security specification.Comment: In Proceedings F-IDE 2014, arXiv:1404.578

Leveraging Crowdsourcing Data For Deep Active Learning - An Application: Learning Intents in Alexa

This paper presents a generic Bayesian framework that enables any deep learning model to actively learn from targeted crowds. Our framework inherits from recent advances in Bayesian deep learning, and extends existing work by considering the targeted crowdsourcing approach, where multiple annotators with unknown expertise contribute an uncontrolled amount (often limited) of annotations. Our framework leverages the low-rank structure in annotations to learn individual annotator expertise, which then helps to infer the true labels from noisy and sparse annotations. It provides a unified Bayesian model to simultaneously infer the true labels and train the deep learning model in order to reach an optimal learning efficacy. Finally, our framework exploits the uncertainty of the deep learning model during prediction as well as the annotators' estimated expertise to minimize the number of required annotations and annotators for optimally training the deep learning model. We evaluate the effectiveness of our framework for intent classification in Alexa (Amazon's personal assistant), using both synthetic and real-world datasets. Experiments show that our framework can accurately learn annotator expertise, infer true labels, and effectively reduce the amount of annotations in model training as compared to state-of-the-art approaches. We further discuss the potential of our proposed framework in bridging machine learning and crowdsourcing towards improved human-in-the-loop systems

Observing the Uptake of a Language Change Making Strings Immutable

To address security concerns, a major change was introduced to the OCaml language and compiler which made strings immutable and introduced array of bytes as replacement for mutable strings. The change is progressively being pushed so that ultimately strings will be immutable. We have investigated the way OCaml package developers undertook the change. In this paper we report on a preliminary observation of software code from the main OCaml package management system. For this purpose we instrumented versions of the OCaml compiler to get precise information into the uptake of safe strings