Semi-endogenous versus Schumpeterian growth models: testing the knowledge production function using international data

Using various indicators of innovative activity and product variety in the OECD countries over the past century, this paper tests first- and second-generation models of economic growth. The estimation results give evidence in favour of Schumpeterian models, while the semi-endogenous growth theories are shown not to be consistent with the data.      

Barriers to innovation through public procurement: A supplier perspective

Public procurement is increasingly viewed as having important potential to drive innovation. Despite this interest, numerous barriers prevent the public sector from acting as an intelligent and informed customer. This paper seeks to understand how barriers related to processes, competences, procedures and relationships in public procurement influence suppliers? ability to innovate and to reap the benefits of innovation. We address this by exploiting a dedicated survey of public sector suppliers in the UK, using a probit model to investigate the influence of structural, market and innovation determinants on suppliers? perception of these barriers.     

What Explains the Success or Failure of Structural Adjustment Programmes?

This paper analyses the causes of success or failure of adjustment programmes, using a new database on 220 reform programmes. We find that the success or failure of reform depends on domestic political-economy forces. A few donor-effort variables are also highly correlated with the probability of success. However, once these effort variables are treated as endogenous, there is no relationship between any of them and the success or failure of reform. These results have clear implications for how the international community should approach policy-based aid.     

Online distributed learning in wind power forecasting

Forecasting wind power generation up to a few hours ahead is of the utmost importance for the efficient operation of power systems and for participation in electricity markets. Recent statistical learning approaches exploit spatiotemporal dependence patterns among neighbouring sites, but their requirement of sharing confidential data with third parties may limit their use in practice. This explains the recent interest in distributed, privacy preserving algorithms for high-dimensional statistical learning, e.g. with auto-regressive models. The few approaches that have been proposed are based on batch learning. However, these approaches are potentially computationally expensive and do not allow for the accommodation of nonstationary characteristics of stochastic processes like wind power generation. This paper closes the gap between online and distributed optimisation by presenting two novel approaches that recursively update model parameters while limiting information exchange between wind farm operators and other potential data providers. A simulation study compared the convergence and tracking ability of both approaches. In addition, a case study using a large dataset from 311 wind farms in Denmark confirmed that online distributed approaches generally outperform existing batch approaches while preserving privacy such that agents do not have to actively share their private data.     

Does the impact of financial liberalization on income inequality depend on financial development? Some new evidence

Instead of empirically finding that higher levels of financial development reduce the positive impact of financial liberalization on inequality, as others do, we come up with the opposite result: financial development strengthens the inequality-raising impact of financial liberalization. We suggest that by, e.g., allowing financial liberalization to lead to more volatility and uncertainty, the model of Bumann and Lensink (2016 “Capital Account Liberalization and Income Inequality.“ Journal of International Money and Finance 61: 143–162.) can be extended as such that also an amplifying instead of reducing effect of financial depth on the impact of financial liberalization on income inequality can be theoretically justified.     

Understanding economic openness: a review of existing measures

Review of World Economics - This paper surveys measures of economic openness, the latter being understood as the degree to which non-domestic actors can or do participate in a domestic economy....     

Economic Growth and (Re-)Distributive Policies in a Non-cooperative World

Many models show that redistribution is bad for growth. This paper argues that in a non-cooperative world optimizing, redistributing (“left-wing”) governments mimic non-redistributing (“right-wing”) policies for fear of capital loss if capital markets become highly integrated and the countries are technologically similar. “Left-right” competition leads to more redistribution and lower GDP growth than “left-left” competition. Efficiency differences allow for higher GDP growth and more redistribution than one's opponent. Irrespective of efficiency differences, however, “left-wing” governments have higher GDP growth when competing with other “left-wing” governments. The results may explain why one observes a positive correlation between redistribution and growth across countries, and why capital inflows and current account deficits may be good for relatively high growth.     

Preferential rules of origin—A conceptual outline

The European Community’s preferential trading agreements with third countries all contain origin rules, which lay down a number of detailed criteria that must be met in order for goods to qualify for preferential customs treatment. These “preferential rules of origin” are currently under discussion by policy-makers¹ and economists developing guidelines for policy-makers. However, no such discussion is apparent in the more recent academic literature. It appears that scientific debate so far has not analysed in depth the basic legal concepts and instruments contained in preferential trading agreements. The following article attempts to identify these instruments and draft a conceptual overview.     

Measuring central bank independence: a latent variables approach

We argue that central bank independence (CBI) is a latent variable of which the various existing quantifications are imperfect indicators. We show how factor analysis techniques can be employed to assess the quality of the various indicators, and how an optimal weighting of the indicators can be obtained that gives the best approximation of CBI. We also show how these results can be utilized in models in which CBI is an explanatory variable. In contrast to the well‐known study of Campillo and Miron (1997) , we find that our CBI indicator is significantly related to inflation, also when various control variables are included.     

Predictors of glycemic control and diabetes-related costs among type 2 diabetes patients initiating therapy with liraglutide in the United States

Objective:

Liraglutide has been shown to significantly improve glycemic control and reduce body weight while minimizing the risk of hypoglycemia in adult patients with type 2 diabetes (T2D). This study aimed to identify characteristics that predict clinical and economic outcomes associated with liraglutide therapy in clinical practice in the US.

Methods:

Using the Truven Health MarketScan Laboratory Database, glycemic control (A1C <7%) and diabetes-related costs were evaluated in T2D patients initiating liraglutide between January 1, 2010 and June 30, 2012. Patients were required to have ≥1 post-index claim for liraglutide and A1C values at baseline and 6 months follow-up. All valid values of baseline A1C were included. Patients previously treated with GLP-1 receptor agonist(s) or insulin, or with evidence of type 1 diabetes, pregnancy, or gestational diabetes during the study period were excluded. Multivariable regression models were used to identify predictors of glycemic control and diabetes-related costs.

Results:

Of 417 patients newly treated with liraglutide, 54.0% achieved glycemic control (A1C <7%) during follow-up. Factors associated with increased odds of glycemic control during follow-up were: being female, POS/EPO health plan type, baseline A1C, early liraglutide initiation (0–1 prior oral anti diabetics [OADs] vs ≥2), adherence to liraglutide (defined as the proportion of days covered [PDC]), and diabetic retinopathy. Being female, earlier liraglutide initiation (0–1 prior OADs), and higher patient share of liraglutide costs were associated with significantly lower diabetes-related costs during follow-up. Factors associated with significantly higher post-index diabetes-related costs were: higher baseline A1C, baseline use of sulfonylureas, and diabetic retinopathy.

Conclusions:

Within this commercially-insured population of T2D patients treated with liraglutide, gender, baseline A1C, early liraglutide initiation (0–1 prior OADs), diabetic retinopathy, better adherence, and patient share of liraglutide costs were associated with increased odds of achieving glycemic control and the odds of having higher or lower diabetes-related costs.