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We will be asking ourselves if the trading blocs created or renewed since the end of the 1980s favor the multilateralization of trade, and so constitute building or stumbling blocks. In a gravity model using panel data, we estimate a set of three regional dummies representative of intra-bloc trade, extra-bloc exports and extra-bloc imports. Taking the resulting three coefficients as a starting point, we propose an original typology of trade creations / diversions and of trading blocs. In applying it to our results, all the groups chosen as well as the Economic and Monetary Union, are shown to be building blocks. No trade diversion is noted, with the exception of an export diversion brought about by North American Free Trade Agreement.

With production activity tending rapidly towards international fragmentation, this study examines the consequences for labour countries of the forms of specialisation brought about by fragmentation processes. It further addresses the risk that fragmented sectors may become excluded from greater developments within the manufacturing industry as a whole. An empirical analysis using panel data reveals that, contrary to expectation, the textile and clothing sector in labour countries does not always reap the positive benefits of this form of international trade integration. Rather, we observe a phenomenon of immiserising specialisation, due to a drop in relative wages within this sector.

This is a pre-print of an article published in Computational Economics. The final authenticated version is available online at: https://doi.org/10.1007/s10614-019-09879-x In this paper, we develop a very flexible and comprehensive state-space framework for modeling time series data. Our research extends the simple canonical model usually employed in the literature, into a panel-data time-varying parameters framework, combining fixed (both common and country-specific) and varying components. Under some specific circumstances, this setting can be understood as a mean-reverting panel time-series model, where the mean fixed parameter can, at the same time, include a deterministic trend. Regarding the transition equation, our structure allows for the estimation of different autoregressive alternatives, and include control instruments, whose coefficients can be set-up either common or idiosyncratic. This is particularly useful to detect asymmetries among individuals (countries) to common shocks. We develop a GAUSS code that allows for the introduction of restrictions regarding the variances of both the transition and measurement equations. Finally, we use this empirical framework to test for the Feldstein–Horioka puzzle in a 17-country panel. The results show its usefulness for solving complexities in macroeconomic empirical research.

We examine the impact of a new mobile-based, dockless bike-sharing service on public transportation. In contrast to traditional rental bikes that are parked at fixed stations, the dockless bikes can be picked up and returned at literally anywhere. This dockless feature of the shared bikes likely provides a solution to the last mile problem, potentially making it a complement to public transportation. Assembling a unique panel data of shared-bike rides and subway traffic, we estimate the relationship between shared-bike ridership and public transportation. Our results show that increases in shared-bike rides lead to increases in subway traffic. This positive effect is stronger for peak hours during weekdays and non-peak hours during weekends. We argue this effect is most likely driven by shared bikes promoting public transportation use and substituting for private cars (substitution effect) and also stimulating new travel (stimulating effect). Overall, we find that dockless shared bikes, in contrast to most of the other sharing economy phenomenon, acts as a complement rather than a substitute for public transportation. In addition, increased use of dockless shared bikes has a positive societal impact, leading to less urban congestion and better environmental protection.

This paper aims to contribute to the longstanding technology-push vs. demand-pull debate and to the literature on renewable energy policy assessment. We argue that in addition to the traditional push–pull dichotomy, the drivers of technological change must be differentiated by whether they are exogenous or endogenous to the economic system and must be assessed with respect to their contribution to both the creation and the diffusion of innovation. We apply this perspective to study innovation in the renewable energy (RE) industry in 15 European Union countries from 1990 to 2012. Using different panel data estimators, we find that public R&D investments, policies supporting RE and per capita income all have a positive effect on either innovation creation or diffusion, whereas the variability of policy support has a negative impact on diffusion. However, impacts are heterogeneous and differ depending on the innovation dimension considered. Most importantly, we find that economic growth is a stronger driver of RE diffusion than technology-push or exogenous demand-pull mechanisms, whereas it is relatively ineffective at stimulating innovation creation. The effect of economic growth on RE diffusion exhibits a nonlinear, U-shaped pattern that resonates with the Environmental Kuznets Curve hypothesis. RE penetration remains negligible at low levels of growth whereas it increases sharply only after income per capita has reached a given threshold. This effect has both a direct cause (with increased affluence demand for environmental quality rises) and an indirect cause (with increased affluence expensive RE policies become more affordable and get implemented more extensively). Our findings have implications for policy making. They suggest that for RE diffusion to increase, innovation policies should be carefully balanced. Government action should be directed not only at shielding renewables from competition with fossil fuel technologies, but also at stimulating aggregated demand and economic growth.

This paper examines the impact of the macro-institutional environment on exploitative-explorative innovation. Building on organizational learning, institutional economics, and innovation studies, we identify country-level institutions that might foster or hinder firms’ incentives and ability to explore or exploit. We test our conjectures by analyzing all patented firm innovations in 22 countries over the 1985-2008 timeframe. Empirical tests demonstrate the role of national institutions in explaining cross-country differences in the level of exploitative and exploratory innovation. The results also suggest that firms’ incentives to explore are influenced by changes in the institutions that regulate the ecology of competition in an economy.

Confronted by increasingly tight budgets and a broad range of alternative options, policy makers need empirical methods to evaluate the effectiveness of policies aimed at supporting the diffusion of renewable energy sources (RES). Rigorous empirical studies of renewable energy policy effectiveness have typically relied on panel data models to identify the most effective mechanisms. A common characteristic of some of these studies, which has important econometric implications, is that they assume that the contribution of RES to total electricity generation will be stationary around a mean. This paper reviews such assumptions and rigorously tests the time series properties of the contribution of RES in the energy mix for the presence of a unit root. To that end, we use both individual and panel unit root tests to determine whether the series exhibit non-stationary behavior at the country level as well as for the panel as a whole. The analysis, applied to a panel of 19 OECD countries over the period 1990-2012, provides strong evidence that the time series of the renewable share of electricity output are not stationary in 17 of the 19 countries examined. This finding has important implications for energy policy assessment and energy policy making, which are discussed in the paper.