The dark side of innovation: How new SKUs affect brand choice in the presence of consumer uncertainty and learning

New product activity is critical for sustained success of consumer packaged goods (CPG) brands. However, the impact of new SKUs on the perceived quality, quality uncertainty and subsequent choice of the brand as a whole is, as of yet, not well understood. The authors study how new additions to the brand line shape consumers’ quality perceptions, and how this – next to the mere line length effect – influences their choice of brands over time. They do so in the setting of an emerging market (China), where new product activity is particularly pervasive. Using a unique scanner panel dataset of Chinese households over the period 2011–2014, they estimate a Bayesian learning model that accommodates varying quality, on two CPG categories, and for two types of new-product additions (new sensory SKUs vs. new non-sensory SKUs). They show that while adding new SKUs may lift the brand’s perceived quality level, it also makes consumers more uncertain about the quality of the brand – dampening their brand choice. This holds especially for light customers – an important part of the brand clientele. Managerial implications are discussed.     

The end of the flat tax experiment in Slovakia: An evaluation using behavioural microsimulation in a dynamic macroeconomic framework

The paper introduces a new way of linking microsimulation models with dynamic general equilibrium frameworks to obtain an evaluation of the impact of detailed tax and benefit measures on the aggregate economy. In the approach presented in this paper, income heterogeneity interacts with the macro-economy via aggregated individual labour supply decisions which influence, and are influenced by, the dynamic evolution of the real wage rate. The method involves a reduced-form representation of the information flow between the macroeconomic and microeconomic blocks. The practical usefulness of the approach is demonstrated by evaluating actual and hypothetical tax reforms that involve abandoning the flat tax system in Slovakia. A hypothetical move to a highly progressive tax structure is shown to generate some employment gains but is associated with a drop in aggregate income and tax revenue.     

Food fraud: economic insights into the dark side of incentives

In this review, we contextualise the articles in this special issue, relating them to existing food fraud research, and identify food fraud research trends, challenges and priorities for the near term. We accomplish these aims through a comprehensive review of research by food scientists, economists, other social scientists, legal experts, government research groups and international trade organisations. Existing food fraud research is heavily weighted towards food science, packaging and labelling, and legal areas of knowledge discovery. Moving forward, research is needed pertaining to general economic welfare outcomes from food fraud incidences, economic incentives to deter frauds, economic spillovers from fraud incidences to other food products and markets (domestic and international) and further delineation of the effect of different types of food fraud on consumer and producer welfare. The articles in this special issue make significant contributions to understanding of the role of food fraud in consumer decisions, measuring consumer welfare losses from fraud, food fraud spillover effects to other markets and new frameworks for fraud analysis.     

Economic Impacts of the Possible China–US Trade War

This article uses a multi-country global general equilibrium (GE) model to numerically simulate the effects of possible China–US trade wars. We introduce an endogenous trade imbalance structure with trade cost into the model which helps to explore both tariff and non-tariff trade war effects. Our simulation results show that China will be significantly hurt by the China–US trade war, but negative impacts are affordable. The US can gain under unilateral sanction measures to China, but will lose if China takes retaliation measures. Comparing the effects under mutual trade war, China will lose more than the US. Introducing non-tariff barrier trade wars will intensify the negative effects, and comparatively negative effects to China are larger than to the US. Mexico’s involvement in trade war with the US will strengthen the negative effects and comparatively hurt the US more. Under non-cooperative and cooperative Nash bargaining equilibrium, the US can gain more than China in trade war negotiation, which means the US has stronger bargaining power than China. Additionally, trade wars between China and the US will hurt most countries and the world especially in GDP and manufacturing employment, but benefit their welfare and trade.     

Intercountry feedback and spillover effects within the international supply and use framework: a Bayesian perspective*

This paper proposes a new framework for the estimation of product-level global and interregional feedback and spillover (FS) factor multipliers. The framework is directly based on interregional supply and use tables (SUTs) that could be rectangular and gives a possibility of taking account of the inherent input–output data uncertainty problems. A Bayesian econometric approach is applied to the framework using the first version of international SUTs in the World Input–Output Database. The obtained estimates of the global and intercountry FS output effects are discussed and presented at the world, country and product levels for the period of 1995–2009.     

On the need to compensate the compensating variation in CGE modeling

The message of this research is that in the standard calibrated setting of Computational General Equilibrium (CGE) models, the welfare measures typically used to compare benchmark with counterfactuals are numéraire dependent. This evaluation bias affects the compensating variation and the Konüs index of cost of living. We show that the equivalent variation is neutral regarding the choice of value units in calibrated models but would be affected as well in uncalibrated CGE models. We illustrate with a simple example and propose an even simpler theoretical solution to overcome these biases; all that is required to have correct welfare estimates is to compensate normalizing with a suitable price index. This type of correction is necessary to overcome the sometimes blind implementation of welfare measures in numerical general equilibrium analysis. We show that the induced quantitative errors may be substantial providing biased welfare estimates and misleading results.     

The behaviour of betting and currency markets on the night of the EU referendum

We study the behaviours of the Betfair betting market and the sterling/dollar exchange rate (futures price) during 24 June 2016, the night of the EU referendum. We investigate how the two markets responded to the announcement of the voting results by employing a Bayesian updating methodology to update prior opinion about the likelihood of the final outcome of the vote. We then relate the voting model to the real-time evolution of the market-determined prices as the results were announced. We find that, although both markets appear to be inefficient in absorbing the new information contained in the vote outcomes, the betting market seems less inefficient than the FX market. The different rates of convergence to the fundamental value between the two markets lead to highly profitable arbitrage opportunities.     

Spatial statistical modelling of insurance risk: a spatial epidemiological approach to car insurance

Spatial models, such as the Besag, York and Mollie (BYM) model, have long been used in epidemiology and disease mapping. A common research question in these subjects is modelling the number of disease events per region; here the BYM models provides a holistic framework for both covariates and dependencies between regions. We use these tools to assess the relative insurance risk associated with the policyholders geographical location. A Bayesian modelling approach is presented and an elastic net is used to reduce the large number of possible geographic covariates. The final inference is performed using Integrated Nested Laplace Approximation. The model is applied to car insurance data from If P&C Insurance together with spatially referenced covariate data of high resolution, provided by Insightone. The entire analysis is performed using freely available R-packages. Including spatial dependence when modelling the number of claims significantly improves on the result obtained using ordinary generalised linear models. However, the support for adding a spatial component to the model for claims cost is weaker.     

Forecasting the UK economy with a medium-scale Bayesian VAR

We estimate a Bayesian VAR (BVAR) for the UK economy and assess its performance in forecasting GDP growth and CPI inflation in real time relative to forecasts from COMPASS, the Bank of England’s DSGE model, and other benchmarks. We find that the BVAR outperformed COMPASS when forecasting both GDP and its expenditure components. In contrast, their performances when forecasting CPI were similar. We also find that the BVAR density forecasts outperformed those of COMPASS, despite under-predicting inflation at most forecast horizons. Both models over-predicted GDP growth at all forecast horizons, but the issue was less pronounced in the BVAR. The BVAR’s point and density forecast performances are also comparable to those of a Bank of England in-house statistical suite for both GDP and CPI inflation, as well as to the official Inflation Report projections. Our results are broadly consistent with the findings of similar studies for other advanced economies.