Time series copulas for heteroskedastic data

We propose parametric copulas that capture serial dependence in stationary heteroskedastic time series. We suggest copulas for first‐order Markov series, and then extend them to higher orders and multivariate series. We derive the copula of a volatility proxy, based on which we propose new measures of volatility dependence, including co‐movement and spillover in multivariate series. In general, these depend upon the marginal distributions of the series. Using exchange rate returns, we show that the resulting copula models can capture their marginal distributions more accurately than univariate and multivariate generalized autoregressive conditional heteroskedasticity models, and produce more accurate value‐at‐risk forecasts.     

Influence of livelihoods on climate change adaptation for smallholder farmers in the Mekong Delta Vietnam

Farmers in the Vietnamese Mekong Delta face a wide range of climate-related and hydrological factors which threaten rice production. Smallholder farmers must adapt to climate change to sustain rice production as their central and most important livelihood activity. A sample was stratified across agro-ecological areas in the Delta affected by flooding, alluvial soils, acid sulphate soils, and saline water intrusion and by derived farmer typologies. A rural livelihoods approach was used in focus group discussions and in-depth interviews to identify and enumerate enabling and constraining adaptation factors. Smallholders experienced diverse natural hazards such as floods, abnormal rains, high temperatures, water scarcity, and salinity intrusion specific to the agro-ecological areas. Adaptation was constrained by labour shortages, water quality, topography, access to combine harvesters, transportation infrastructure, dryers and household savings. Adaptation was enabled by farming techniques and experience, cooperative groups, water quantity, access to information, and ability to purchase agro-chemicals through credit. Small farmers (< 1?ha) were more constrained than large farmers (> 1?ha) who had an expanded livelihood asset base. A range of policy implications are discussed, but adaptation is not just about technological fixes but requires overall improvements in a range of human, social and financial components.     

Introduction to symposium: Smallholders in communist and postcommunist societies

The primary contributions of smallholders during the communist and early postcommunist periods have been food production and labour for large farms. Those conditions are changing, however, as modern farms require less labour and food supply may be imported. For most smallholders in Central and Eastern European and former Soviet Union countries, the postcommunist neoliberal environment has not brought significant improvement, and strong arguments can be made that land grabbing, social and economic exclusion, and rural poverty are worse than regime bias during the communist period. Cooperatives, which have empowered smallholders in other parts of the world, have not been as well developed in postcommunist nations.     

Varieties of paternalism and the heterogeneity of utility structures

A principal source of interest in behavioral economics has been its advertised contributions to policies aimed at ‘nudging’ people away from allegedly natural but self-defeating behavior toward patterns of response thought more likely to improve their welfare. This has occasioned controversies among economists and philosophers around the normative limits of paternalism, especially by technical policy advisors. One recent suggestion has been that ‘boosting,’ in which interventions aim to enhance people’s general cognitive skills and representational repertoires instead of manipulating their choice environments behind their backs, avoids the main normative challenges. A limitation in most of this literature is that it has focused on relatively sweeping policy recommendations and consequently on strong polar alternatives of general paternalism and strict laissez faire. We review a real instance, drawn from a consulting project we conducted for an investment bank, of a proposed intervention that is more typical of the kind that economists are more often actually called upon to offer. In this example, the sophistication of current tools for preference attribution, combined with philosophical externalism about the semantics of preferences that makes it less plausible to attribute their literal self-conscious representation to people as propositional attitude content becomes more tightly refined, blocks applicability of the distinction between nudging and boosting. This seems to call for irreducible, context-specific ethical judgment in assessing the appropriateness of the forms of paternalism that economists must actually wrestle with in going about their everyday business.     

On the quest for supply chain transparency through Blockchain: Lessons learned from two serialized data projects

The ability to look into the supply chain has long enticed SCM scholars and practitioners. The possibilities created by such visibility are endless—from risk reduction and continuity planning to inventory management and cost reduction, nothing is off the table when end‐to‐end visibility is a possibility. Because of such enticements, there is usually much buzz in the industry every time a new technology that promises visibility and transparency is brought forward. Yet, years later, stories sometimes emerge that said technologies either failed to deliver or were not everything they were made out to be. Blockchain is yet another emerging technology in this space. Some consultants promise that it will be the final answer to the transparency and visibility woes that companies currently face. Yet, there is little empirical investigation regarding how the technology may benefit adopters, what the bottlenecks may be, and to what extent it may be able to deliver on these promises, without massive system‐wide upgrades of extant hardware and computing prowess. The current study takes a step in this direction by investigating a blockchain‐driven proof of concept across an industry consortium to identify promises, possibilities, and challenges of blockchain.     

Advertising and brand attitudes: Evidence from 575 brands over five years

Quantitative Marketing and Economics - Little is known about how different types of advertising affect brand attitudes. We investigate the relationships between three brand attitude variables...     

Multi-level and mixed-level <Emphasis Type="Italic">k</Emphasis>-circulant supersaturated designs

Supersaturated designs (SSDs) constitute an important class of fractional factorial designs that could be extremely useful in factor screening experiments. Most of the existing studies have focused on balanced designs. This paper provides a new lower bound for the \(E(f_{NOD})\)-optimality measure of SSDs with general run sizes. This bound is a generalization of existing bounds since it is applicable to both balanced and unbalanced designs. Optimal multi and mixed-level, balanced and nearly balanced SSDs are constructed by applying a k-circulant type methodology. Necessary and sufficient conditions are introduced for the generator vectors, in order to pre-ensure the optimality of the constructed k-circulant SSDs. The provided lower bounds were used to measure the efficiency of the generated designs. The presented methodology leads to a number of new families of improved SSDs, providing tools for directly constructing optimal or nearly-optimal k-circulant designs by just checking the corresponding generator vector.     

The Impact of Automated Reminders on Credit Outcomes: Results from an Experimental Pilot Program

This study evaluates the impact of an automated reminder program designed to help credit counseling consumers manage their payment obligations and financial goals. Credit counseling consumers were randomly assigned to receive reminders linked to their financial goals and payment obligations for one year after an initial credit counseling session. We find that consumers offered reminders were 21% less likely than the control to experience severe (60+ day) payment delinquencies and were 12% less likely to experience a 30+ day delinquency. At the same time, these consumers saw a 10.5 point increase in credit scores relative to the control group. There were no significant impacts on total credit card balances or installment debt levels. This analysis provides promising evidence that automated reminders can provide an important complement to traditional credit counseling when it comes to improving consumers' credit profiles and does so at a fairly low cost.