Inflation and income inequality: A link through the job-search process

In this paper I devise a new channel by means of which the (empirically documented) positive correlation between ináation and income inequality can be understood. Available empirical evidence reveals that ináation increases wage dispersion. For this reason, the higher the ináation rate, the higher turns out to be the beneÖt, for a worker, of making additional draws from the distribution of wages, before deciding whether to accept or reject a job o§er. Assuming that some workers have less access to information (wage o§ers) than others, I show that the Gini coe¢ cient of income distribution turns out to be an increasing function of the wage dispersion and, consequently, of the rate of ináation. Two examples are provided to illustrate the mechanism.

The missing link: using the NBER recession indicator to construct coincident and leading indices economic activity

We use the information content in the decisions of the NBER Business Cycle Dating Committee to construct coincident and leading indices of economic activity for the United States. We identify the coincident index by assuming that the coincident variables have a common cycle with the unobserved state of the economy, and that the NBER business cycle dates signify the turning points in the unobserved state. This model allows us to estimate our coincident index as a linear combination of the coincident series. We establish that our index performs better than other currently popular coincident indices of economic activity.

The missing link: using the NBER recession indicator to construct coincident and leading indices economic activity

We use the information content in the decisions of the NBER Business Cycle Dating Committee to construct coincident and leading indices of economic activity for the United States. We identify the coincident index by assuming that the coincident variables have a common cycle with the unobserved state of the economy, and that the NBER business cycle dates signify the turning points in the unobserved state. This model allows us to estimate our coincident index as a linear combination of the coincident series. We establish that our index performs better than other currently popular coincident indices of economic activity.

The missing link: using the NBER recession indicator to construct coincident and leading indices economic activity

We use the information content in the decisions of the NBER Business Cycle Dating Committee to construct coincident and leading indices of economic activity for the United States. We identify the coincident index by assuming that the coincident variables have a common cycle with the unobserved state of the economy, and that the NBER business cycle dates signify the turning points in the unobserved state. This model allows us to estimate our coincident index as a linear combination of the coincident series. We compare the performance of our index with other currently popular coincident indices of economic activity.

Measurements of income inequality: a critique. Inflation and income inequality: a link through the job- search process

In this paper I claim that, in a long-run perspective, measurements of income inequality, under any of the usual inequality measures used in the literature, are upward biased. The reason is that such measurements are cross-sectional by nature and, therefore, do not take into consideration the turnover in the job market which, in the long run, equalizes within-group (e.g., same-education groups) inequalities. Using a job-search model, I show how to derive the within-group invariant-distribution Gini coefficient of income inequality, how to calculate the size of the bias and how to organize the data in arder to solve the problem. Two examples are provided to illustrate the argument.

Mhealth entrepreneurship: an exploratory research for a managerial model for mhealth start ups in low and middle income countries

Since some years, mobile technologies in healthcare (mHealth) stand for the transformational force to improve health issues in low- and middle-income countries (LMICs). Although several studies have identified the prevailing issue of inconsistent evidence and new evaluation frameworks have been proposed, few have explored the role of entrepreneurship to create disruptive change in a traditionally conservative sector. I argue that improving the effectiveness of mHealth entrepreneurs might increase the adoption of mHealth solutions. Thus, this study aims at proposing a managerial model for the analysis of mHealth solutions from the entrepreneurial perspective in the context of LMICs. I identified the Khoja–Durrani–Scott (KDS) framework as theoretical basis for the managerial model, due to its explicit focus on the context of LMICs. In the subsequent exploratory research I, first, used semi-structured interviews with five specialists in mHealth, local healthcare systems and investment to identify necessary adaptations to the model. The findings of the interviews proposed that especially the economic theme had to be clarified and an additional entrepreneurial theme was necessary. Additionally, an evaluation questionnaire was proposed. In the second phase, I applied the questionnaire to five start-ups, operating in Brazil and Tanzania, and conducted semi-structured interviews with the entrepreneurs to gain practical insights for the theoretical development. Three of five entrepreneurs perceived that the results correlated with the entrepreneurs' expectations of the strengths and weaknesses of the start-ups. Main shortcomings of the model related to the ambiguity of some questions. In addition to the findings for the model, the results of the scores were analyzed. The analysis suggested that across the participating mHealth start-ups the ‘behavioral and socio-technical’ outcomes were the strongest and the ‘policy’ outcomes were the weakest themes. The managerial model integrates several perspectives, structured around the entrepreneur. In order to validate the model, future research may link the development of a start-up with the evolution of the scores in longitudinal case studies or large-scale tests.