R&D productivity rides again?

A recent analysis of R&D productivity suggests that there are grounds for ‘cautious optimism’ that the industry ‘turned the corner’ in 2008 and is ‘on the comeback trail’. We believe that this analysis is flawed and most probably wrong. We present an alternative analysis of these same data to suggest that the industry is not yet ‘out of the woods’ and suggest that many of the systemic issues affecting pharmaceutical R&D productivity are still being resolved. Copyright © 2014 John Wiley & Sons, Ltd.     

Generalisation of Mood's Test to Factorial Designs to Detect Heterogeneity of Variances

Mood's test, which is a relatively old test (and the oldest non‐parametric test among those tests in its class) for determining heterogeneity of variance, is still being widely used in different areas such as biometry, biostatistics and medicine. Although it is a popular test, it is not suitable for use on a two‐way factorial design. In this paper, Mood's test is generalised to the 2 × 2 factorial design setting and its performance is compared with that of Klotz's test. The power and robustness of these tests are examined in detail by means of a simulation study with 10,000 replications. Based on the simulation results, the generalised Mood's and Klotz's tests can especially be recommended in settings in which the parent distribution is symmetric. As an example application we analyse data from a multi‐factor agricultural system that involves chilli peppers, nematodes and yellow nutsedge. This example dataset suggests that the performance of the generalised Mood test is in agreement with that of the generalised Klotz's test.     

Computing first-order sensitivity indices with contribution to the sample mean plot

In this paper, we investigate the use of the contribution to the sample mean plot (CSM plot) as a graphical tool for sensitivity analysis (SA) of computational models. We first provide an exact formula that links, for each uncertain model input X_j, the CSM plot C_j(·) with the first-order variance-based sensitivity index S_j. We then build a new estimate for S_j using polynomial regression of the CSM plot. This estimation procedure allows the computation of S_j from given data, without any SA-specific design of experiment. Numerical results show that this new S_j estimate is efficient for large sample sizes, but that at small sample sizes it does not compare well with other S_j estimation techniques based on given data, such as the effective algorithm for computing global sensitivity indices method or metamodel-based approaches.     

Statistical Inference Based on Progressively Type II Censored Data from Weibull Model

In this article, we consider the problem of estimating the shape and scale parameters and predicting the unobserved removed data based on a progressive type II censored sample from the Weibull distribution. Maximum likelihood and Bayesian approaches are used to estimate the scale and shape parameters. The sampling-based method is used to draw Monte Carlo (MC) samples and it has been used to estimate the model parameters and also to predict the removed units in multiple stages of the censored sample. Two real datasets are presented and analyzed for illustrative purposes and Monte carlo simulations are performed to study the behavior of the proposed methods.     

Estimation for the Parameters of Generalized Half-normal Distribution Based on Progressive Type-I Interval Censoring

Based on progressively Type-I interval censored sample, the problem of estimating unknown parameters of a two parameter generalized half-normal(GHN) distribution is considered. Different methods of estimation are discussed. They include the maximum likelihood estimation, midpoint approximation method, approximate maximum likelihood estimation, method of moments, and estimation based on probability plot. Several Bayesian estimates with respect to different symmetric and asymmetric loss functions such as squared error, LINEX, and general entropy is calculated. The Lindley’s approximation method is applied to determine Bayesian estimates. Monte Carlo simulations are performed to compare the performances of the different methods. Finally, analysis is also carried out for a real dataset.     

MONITORING IN TEAMS: USING LABORATORY EXPERIMENTS TO STUDY A THEORY OF THE FIRM

Alchian and Demsetz’s influential explanation of the classical business firm (The American Economic Review, 1972, 62, 777–795) argues that there is need for a concentrated residual claim in the hands of a central agent, to motivate the monitoring of workers. We model monitoring as a way to transform team production from a collective action dilemma with strong free riding incentives to a productivity‐enhancing opportunity with strong private marginal incentives to contribute effort. In an experiment, we have subjects experience team production without monitoring, team production with a central monitor, and team production with peer monitoring. Then subjects vote on whether to employ the central monitor, who gets to keep a fixed share of the team output, or to rely on peer monitoring, which entails a coordination or free riding problem. Our subjects usually prefer peer monitoring but they switch to the specialist when unable to successfully self‐monitor. We provide evidence for situations in which team members resist the appointing of a central monitor and succeed in overcoming coordination and free riding problems as well as for a situation in which an Alchian–Demsetz‐like firm grows in the laboratory.     

WORKERS,WARRIORS, AND CRIMINALS: SOCIAL CONFLICT IN GENERAL EQUILIBRIUM

We incorporate appropriation activities (social conflict) into canonical models of trade and study how economic shocks and policies affect the intensity of conflict. We show that not all shocks that could make society richer reduce conflict: positive shocks to labor‐intensive industries diminish conflict, while positive shocks to capital‐intensive industries increase it. The key requirement is that conflict activities be more labor intensive than the economy as this determines how shocks affect the returns and costs of conflict. Our theory is consistent with several observed patterns of conflict and implies that empirical work should take into account the relative factor intensities of the productive and conflict sectors in each country. Incorporating appropriation into a canonic general equilibrium model affects what policies may be deemed desirable: in order to reduce conflict and generate Pareto‐improvements policy must be distortionary, while reforms that appear efficiency‐enhancing under the unrealistic assumption of perfect property rights may backfire. This offers one explanation for why reforms based on traditional models without appropriation may be delayed and become unpopular when implemented, and why societies may sympathize with seemingly inefficient redistribution.     

DO HOUSE PRICES DRIVE CONSUMPTION GROWTH? THE COINCIDENT CYCLES OF HOUSE PRICES AND CONSUMPTION IN THE UK

This paper uses a realistic structural lifecycle model of consumption and housing decisions to understand how data might distinguish different mechanisms that explain the correlation between house prices and consumption. The model includes price and earnings shocks estimated from data (the latter including aggregate and idiosyncratic components), and incorporates realistic features of the UK mortgage market. We simulate the model using more than 30 years of realized shocks and under counterfactual scenarios. Our results confirm the intuition of earlier studies: house price shocks should have a larger effect on the consumption of older households and earnings shocks on young households.     

IS THE ELASTICITY OF INTERTEMPORAL SUBSTITUTION CONSTANT?

In all common models of inter‐temporal allocation, the assumption of a constant elasticity of intertemporal substitution (EIS) imposes surprising limitations on within‐period budget allocations. Consequently, the constant EIS assumption can be tested with demand data. In fact, the EIS is pinned down completely by the shape of Engel curves: if the EIS is constant then the EIS can be estimated without variation in the interest rate. That a price elasticity can be estimated without variation in the relevant price illustrates just how strong the constant EIS assumption is. The constant EIS assumption is rejected by demand data.     

ECONOMIC INTEGRATION,POLITICAL INTEGRATION OR BOTH?

We study the effects of economic and political integration by presenting a model in which firms compete with each other in both an economic market—where they produce a good and compete for market share—and in a political (rent seeking) market—where they compete for transfers from the government. Growth is driven by firms’ cost‐reducing innovation activity and economic and political integration affect firms’ incentive to innovate differently. In this setting, economic and political integration can be seen as complementary. Economic integration, when not accompanied by political integration, can lead to less innovation and slower growth as firms respond to increased competition in the economic market by focusing more on rent‐seeking activity. When economic integration is accompanied by political integration, innovation and growth will be stronger and welfare higher.