The Economic and Climate Value of Flexibility in Green Energy Markets

Environmental and Resource Economics - This paper examines how enhanced flexibility across space, time, and a regulatory dimension affects the economic costs and CO $$_2$$ emissions of integrating...     

Reinforcement learning and stochastic optimisation

At the heart of financial mathematics lie stochastic optimisation problems. Traditional approaches to solving such problems, while applicable to broad classes of models, require specifying a model to complete the analysis and obtain implementable results. Even then, the curse of dimensionality challenges the viability of conventional methods to settings of practical relevance. In contrast, machine learning, and reinforcement learning (RL) particularly, promises to learn from data and overcome the curse of dimensionality simultaneously. This article touches on several approaches in the extant literature that are well positioned to merge our traditional techniques with RL.

     

Dynamics of public opinion and policy response under proportional and plurality elections

We compare the patterns of adjustment of government policy to changes in public opinion in the Netherlands and the United Kingdom. These countries are similar in many ways, except that the United Kingdom has plurality elections and single-party government, while the Netherlands has proportional representation (PR) and coalition government. This provides the first application of the Macro Polity approach to a country with PR elections. We find that government policy in the Netherlands is highly responsive to public opinion. This cannot be the result of alternation of government, but instead must be the result of some other process, such as coalition bargaining. In the United Kingdom, however, the dynamic of adjustment is far more complex. Alternation of government does not produce responsiveness, but rather seems to get in the way of it. This leads to an over-correction dynamic in which policy can be out of line with public opinion for long periods of time.     

Obviousness around the clock

Experimental Economics - Li (Am Econ Rev 107(11):3257–3287, 2017) introduces a theoretical notion of obviousness of a dominant strategy, to be used as a refinement in mechanism design. This...     

Modeling intensification decisions in the Kilombero Valley floodplain: A Bayesian belief network approach

The Kilombero Valley floodplain in Tanzania is a major agricultural area. Government initiatives and projects supported by international funding have long sought to boost productivity. Due to increasing population pressure, smallholder farmers are forced to increase their output. Nevertheless, the level of intensification is still lower than what is considered necessary to increase production and support smallholder livelihoods significantly. This article aims to better understand farmers’ intensification choices and their interdependent determinants. We propose a novel modeling approach for identifying determinants of intensification and their interrelationships by combining a Bayesian belief network (BBN), experimental design, and multivariate regression trees. Our approach complements existing lower-dimensional statistical models by considering uncertainty and providing an easily updatable model structure. The BBN is constructed and calibrated using data from a survey of 304 farm households. Our findings show how the data-driven BBN approach can be used to identify variables that influence farmers’ decision to choose one technique over another. Furthermore, the most important drivers vary widely, depending on the intensification options being considered.     

The power of online panel paradata to predict unit nonresponse and voluntary attrition in a longitudinal design

The objective of this study is to identify factors affecting participation rates, i.e., nonresponse and voluntary attrition rates, and their predictive power in a probability-based online panel. Participation for this panel had already been investigated in the literature according to the socio-demographic and socio-psychological characteristics of respondents and different types of paradata, such as device type or questionnaire navigation, had also been explored. In this study, the predictive power of online panel participation paradata was instead evaluated, which was expected (at least in theory) to offer even more complex insight into respondents’ behavior over time. This kind of paradata would also enable the derivation of longitudinal variables measuring respondents’ panel activity, such as survey outcome rates and consecutive waves with a particular survey outcome prior to a wave (e.g., response, noncontact, refusal), and could also be used in models controlling for unobserved heterogeneity. Using the Life in Australia? participation data for all recruited members for the first 30 waves, multiple linear, binary logistic and panel random-effect logit regression analyses were carried out to assess socio-demographic and online panel paradata predictors of nonresponse and attrition that were available and contributed to the accuracy of prediction and the best statistical modeling. The proposed approach with the derived paradata predictors and random-effect logistic regression proved to be reasonably accurate for predicting nonresponse—with just 15 waves of online panel paradata (even without sociodemographics) and logit random-effect modeling almost four out of five nonrespondents could be correctly identified in the subsequent wave.

     

Quantifying Bias and Inaccuracy of Upper-Level Aggregation in the Harmonised Index of Consumer Prices for Germany and the Euro Area

Current measurement practices of the Harmonised Index of Consumer Prices (HICP) produce an upward bias of about one-ninth of a percentage point in German inflation due to changing consumption being disregarded and preliminary data being used in the compilation of expenditure weights. The statistical uncertainty produced by these sources of mismeasurement can be illustrated by an interdecile range of about one-quarter of a percentage point. The annual updating of the quantity component of the weights, implemented in 2012, has reduced the substitution component, making the disregard of changing consumption virtually a non-issue for the euro area HICP. The measurement of the German HICP is impaired by the extrapolation of expenditure weights. The use of preliminary national accounts data since 2012 has not led to an improvement. This source of mismeasurement is likely to be relevant for the euro area HICP as well but cannot be quantified due to data constraints.     

The attractiveness of Indian Polytechnics graduates—An analysis from the (demand-side) perspective of companies and colleges

The paper examines the attractiveness of graduates from Indian Polytechnics (PTs). The attractiveness is examined from the perspective of actors who have a demand for the graduates, namely companies and engineering colleges. To understand the reasons for their assessment of attractiveness, this study uses the concept of institutional logics (ILs) to unveil the inherent reasons behind the stakeholders' perception of attractiveness. To understand the stakeholders' ILs, interviews were undertaken in nine companies and 10 colleges in Mumbai and Delhi. The findings make clear that the companies' and colleges' assessments of the attractiveness of PT graduates are very different, reflecting their own ILs. Companies assess the attractiveness as limited due to the lack of employability of PT graduates. In contrast, colleges view graduates far more positively, as the weaknesses described by companies have less of an impact on them.     

Values-Based and Global Systemically Important Banks: Their Stability and the Impact of Regulatory Changes After the Financial Crisis on it

Asia-Pacific Financial Markets - We study the financial stability of Values-Based Banks (VBBs) and Global Systemically Important Banks (GSIBs), and how regulatory changes in the aftermath of the...     

Green and Sustainable Finance in the Asia-Pacific Markets: An Introduction to the Special Issue

Asia-Pacific Financial Markets -