The fallacy of giving advice

Have you ever been micro-managed? Have you ever been told ‘to the letter’ what to do in a given situation? Or maybe as a leader you have also fallen into the trap of giving advice? We challenge the assumption that leaders should have the answer for everything. Occasionally, directing works, however, do it too often and at one point, it will turn out to be bad advice. The logical consequence is that leaders work on and increase the quality of the advice they give. We showcase that the alternative to leaders giving ‘bad’ advice is to not give advice at all. We shed light on the concept of leaders acting as coaches and how leaders can empower others to find their own answers. Specifically, we highlight four mind shifts in which leaders can engage if they want to use a coaching style: from ignoring emotions to empathy, from directing to empowering, from problem-focused to solution-focused and from weakness to strengths.     

Integrating expected coverage and local reliability for emergency medical services location problems

Daskin's MEXCLP model [Daskin M. A maximum expected covering location model: formulation, properties, and heuristic solution. Transportation Science 1983;17:48-70] was one of the first efforts to capture the stochastic nature of emergency medical services (EMS) location problems within a mixed-integer formulation. With their subsequent introduction of MALP, ReVelle and Hogan [The maximum availability location problem. Transportation Science 1989;23:192-200] offered two key advances, local vehicle busyness estimates and the α-reliability objective. While these constructs have influenced many subsequent EMS location models, they have been subjected to relatively little empirical analysis. To address this, we introduce the LR-MEXCLP, a hybrid model combining the local busyness estimates of MALP with the maximum coverage objective of MEXCLP. We then solve a series of problems with all three models and employ simulation to estimate aggregate service levels. We find that LR-MEXCLP leads to modest but consistent service gains over both MALP and MEXCLP. These results support the merits of local busyness estimates, but they also suggest that the α-reliability objective may be inappropriate when seeking to maximize aggregate system response capabilities. More generally, our research underscores the utility of (a) linking modeling assumptions and goals with real-world application contexts, and (b) employing simulation or other techniques to validate theoretical results.     

Estimation of data measured with error and subject to linear restrictions

Variables are often measured subject to error, whether they are collected as part of an experiment or by sample surveys. A consequence of this is that there will be different estimates of the same variable, or, more generally, linear restrictions which the observations should satisfy but fail to. With knowledge of the variances of the various observations, it has been shown elsewhere that maximum-likelihood estimates of the observations can be produced. This paper shows how, given a sequence of such observations, estimates can be produced without knowledge of data reliabilities. The method is applied to estimates of constant price US GNP. It suggests that 64 per cent of the discrepancy should be attributed to the expenditure estimate, with only 36 per cent going to the income/output estimate. The current method of presentation, on the other hand, places the whole of the error in the income/output estimate.     

Biased recommendations from biased and unbiased experts

When can you trust an expert to provide honest advice? We develop and test a recommendation game where an expert helps a decision maker choose among two actions that benefit the expert and an outside option that does not. For instance, a salesperson recommends one of two products to a customer who may instead purchase nothing. Subject behavior in a laboratory experiment is largely consistent with predictions from the cheap talk literature. For sufficient symmetry in payoffs, recommendations are persuasive in that they raise the chance that the decision maker takes one of the actions rather than the outside option. If the expert is known to have a payoff bias toward an action, such as a salesperson receiving a higher commission on one product, the decision maker partially discounts a recommendation for it and is more likely to take the outside option. If the bias is uncertain, then biased experts lie even more, whereas unbiased experts follow a political correctness strategy of pushing the opposite action so as to be more persuasive. Even when the expert is known to be unbiased, if the decision maker already favors an action the expert panders toward it, and the decision maker partially discounts the recommendation. The comparative static predictions hold with any degree of lying aversion up to pure cheap talk, and most subjects exhibit some limited lying aversion. The results highlight that the transparency of expert incentives can improve communication, but need not ensure unbiased advice.     

Measuring the costs of children: parametric and semiparametric estimators1

How much additional income does a family with four children need to attain the same welfare level as a family with two children? And how much does a single person need compared to a childless couple? These questions are important in applied micro-economics and underlie public policy on, for example, social benefits and child allowances. In microeconomics, this is known as the problem of measuring equivalence scales. We estimate these scales using two types of subjective survey information. First, we use answers to survey questions on the income required to attain a given utility level. We compare the results for the usual linear model with semiparametric estimates, in which the functional form of the relationship between required income and family size and actual income is left unspecified. Second, we use answers to the question: how satisfied are you with actual household income? We present parametric and semiparametric estimates for ordered response models explaining this discrete variable. We find that according to the second type of information, costs of children are much larger than according to the first.     

Combining Opinions for Use in Bayesian Networks: A Measurement Error Approach

Bayesian networks (BNs) are graphical probabilistic models used for reasoning under uncertainty. These models are becoming increasingly popular in a range of fields including engineering, ecology, computational biology, medical diagnosis and forensics. In most of these cases, the BNs are quantified using information from experts or from users' opinions. While this quantification is straightforward for one expert, there is still debate about how to represent opinions from multiple experts in a BN. This paper proposes the use of a measurement error model to achieve this. The proposed model addresses the issues associated with current methods of combining opinions such as the absence of a coherent probability model, the loss of the conditional independence structure of the BN and the provision of only a point estimate for the consensus. The proposed model is applied to a subnetwork (the three final nodes) of a larger BN about wayfinding in airports. It is shown that the approach performs well than do existing methods of combining opinions.     

Estimates of the return to schooling in Sweden from a large sample of twins

A large sample of twins was used to examine whether conventional estimates of the return to schooling in Sweden are biased because ability is omitted from the earnings–schooling relationship. Ignoring measurement error, the results indicate that omitting ability from the earnings–schooling relationship leads to estimates that are positively biased. However, reasonable estimates of the measurement-error-adjusted returns are both above and below the unadjusted estimates, showing that the results depend crucially on a parameter not known at this time. However, an estimate of the reliability ratio was obtained using two measures on educational attainment. With this estimate of the reliability ratio, the measurement-error-adjusted estimate of the return to schooling in the sample of identical twins indicates that there is at most a slight ability bias in the conventional estimates of the return to schooling. The fundamental assumption of this kind of study is that within-pair differences in educational attainment are randomly determined. This assumption was also tested, but no strong evidence to reject it was found.     

Het vergelijken van twee verschillende schatters voor een percentiel P van een normale verdeling

A comparison is made between two different methods to estimate the probability that a normally distributed observation is less than a certain value. One method is based on the binomial distribution, the other one on HALD'S maximum likelihood estimates of the parameters of a censored normal distribution. For large sample sizes a graph of the relative efficiency of these two estimates is constructed. A sampling experiment was performed in order to investigate for one particular situation the possible bias of HALD'S maximum likelihood estimate, which is only asymptotically unbiassed.     

Recursions for the two-stage least-squares estimators

This paper presents recursion formulae for the two-stage least-squares estimators of the structural coefficients in a simultaneous equation model and for the residual sum of squares used in estimating the asymptotic covariance matrix. Included are formulae for updating estimates when a new set of observations is obtained and for revising estimates when a set of observations is discarded. The recursion formulae should prove to be of both practical and theoretical interest to econometricians.     

Hedonic prices,demands for urban housing amenities,and benefit estimates

This paper uses a Rosen, two-step, hedonic price-trait demand approach to estimate demand functions for a vector of urban amenities. To ascertain whether this theoretically preferred approach yields benefit estimates which differ from the oft-used Ridker-Henning, one-step, hedonic approach we conduct a sensitivity analysis. We find that the two-step approach does yield different benefit estimates and that the differences are large for some amenities. The estimates are sensitive to the functional form of the hedonic equation when the forms are significantly different according to modified Box-Cox results, but are not particularly sensitive to specification of the amenity demand equation.     

Estimates of the demand for medical care under different functional forms

We estimate price and income elasticities from a linear, log-linear, and the almost ideal demand model (with and without an adjustment for selectivity bias) in an effort to show that special attention should be paid to the underlying assumptions of consumer behaviour when estimating a medical care demand model. The literature on medical care utilization is extended by incorporating two major components of spending as separate demands in a system of medical care spending. We find that estimates of elasticities vary depending on the functional form of the estimating equation, thus questioning the usefulness for policy purposes of single estimates of elasticities.     

Multivariate Small Area Estimation of Multidimensional Latent Economic Well-being Indicators

Factor analysis models are used in data dimensionality reduction problems where the variability among observed variables can be described through a smaller number of unobserved latent variables. This approach is often used to estimate the multidimensionality of well-being. We employ factor analysis models and use multivariate empirical best linear unbiased predictor (EBLUP) under a unit-level small area estimation approach to predict a vector of means of factor scores representing well-being for small areas. We compare this approach with the standard approach whereby we use small area estimation (univariate and multivariate) to estimate a dashboard of EBLUPs of the means of the original variables and then averaged. Our simulation study shows that the use of factor scores provides estimates with lower variability than weighted and simple averages of standardised multivariate EBLUPs and univariate EBLUPs. Moreover, we find that when the correlation in the observed data is taken into account before small area estimates are computed, multivariate modelling does not provide large improvements in the precision of the estimates over the univariate modelling. We close with an application using the European Union Statistics on Income and Living Conditions data.     

Evaluating the efficiency of Italian public universities (2008–2011) in presence of (unobserved) heterogeneity

In assessing the performance of universities, the most recent literature underlined that the efficiency scores may suffer from the presence of incidental parameters or time-invariant, often unobservable, effects that lead to biased efficiency estimates. To deal with this problem, we apply a procedure developed by [67]; for estimating the efficiency in Italian higher education through a multi-output parametric distance function. We show that models which do not consider unobservable heterogeneity tend to estimate divergent efficiency scores. We also study the determinants of efficiency; the findings provide a clue towards the expansion of pro-competitive policies in the Italian higher education sector, consistently with the interpretation that when market forces operate, there are benefits for university efficiency. When exploring differences in the performance of universities, by geographical areas, we claim that maintaining State-level policies can be detrimental for overall efficiency, and instead special interventions for universities in the South should be designed.     

School district quality and property values: Examining differences along school district boundaries

Examining differences across school district boundaries rather than school attendance zone boundaries has several advantages. These advantages include being applicable when attendance zones are not available or less relevant to educational outcomes as arises with within district school choice and for examining the effect of factors like school spending or property taxes that do not vary within districts. However, school district boundaries have often been in place for many years allowing households to sort based on school quality and potentially creating distinct neighborhoods on either side of boundaries. We estimate models of housing prices using repeated cross-sections of housing transactions near school district boundaries in Connecticut. These models exploit changes over time to control for across boundary differences in neighborhood quality. We find significant effects of test scores on property values, but those effects are notably smaller than both OLS and traditional boundary fixed effects estimates.     

2010影响未来管理那些事儿

2011年,将会发生什么?答案恐怕要从2010年来寻找。——刚刚过去的2010年真可谓多事之秋。国内国际,各个层面的商业事件层出不穷,且常常红黑两面交集,引发出远远超越商业层面的多方反思。它们发生于2010,影响的却将是2011。在征集各方意见之后,我们筛选出14个事件,提炼成14个关键词,力求勾画出2011年的管理图谱。     

The external returns to education: UK evidence using repeated cross-sections

Augmenting a Mincerian earnings function with industry level data we estimate the external return to schooling for a repeated cross-section of individuals in the UK over the period 1994–2004. For men age 30–49 we find that a one year increase in the industry average level of schooling is associated with an increase in individual wages of 2.6 to 3.9%, around 2 to 3 fifths of the private return to schooling. We illustrate the sensitivity of external return estimates to industry ICT use and union density, and individuals' own level of schooling.     

Group-based judgmental forecasting: An integration of extant knowledge and the development of priorities for a new research agenda

We review and integrate the extant knowledge on group-based forecasting, paying particular attention to the papers included in this special issue of the International Journal of Forecasting. We focus on the relative merits of different methods of aggregating individual forecasts, the advantages of heterogeneity in group memberships, the impact of others’ opinions on group members, and the importance of perceptions of trust. We conclude that a change of opinion following group-based deliberation is most likely to be appropriate where the group membership is heterogeneous, the minority opinion is protected from pressure to conform, information exchange between group members has been facilitated, and the recipient of the advice is able — by reasoning processes — to evaluate the reasoning justifying the proffered advice. Proffered advice is least likely to be accepted where the advisor is not trusted — an evaluation which is based on the advisor having different perceived values to the recipient and being thought to be self-interested. In contrast, the outcome of a group-based deliberation is most likely to be accepted when there is perceived to be procedural fairness and the participants in the process are perceived to be trustworthy. Finally, we broaden our discussion of group-based forecasting to include a consideration of other group-based methodologies which are aimed at enhancing judgment and decision making. In particular, we discuss the relevance of research on small-group decision making, the nature and quality of the advice, group-based scenario planning, and public engagement processes. From this analysis, we conclude that, for medium- to long-term judgemental forecasting, a variety of non-outcome criteria need to be considered in the evaluation of alternative group-based methods.     

System economics: Overcoming the pitfalls of forecasting models via a multidisciplinary approach

In areas from medicine to climate change to economics, we are faced with huge challenges and a need for accurate forecasts, yet our ability to predict the future has been found wanting. The basic problem is that complex systems such as the atmosphere or the economy can not be reduced to simple mathematical laws and modeled accordingly. The equations in numerical models are therefore only approximations to reality, and are often highly sensitive to external influences and small changes in parameterisation — they can be made to fit past data, but are less good at prediction. Since decisions are usually based on our best models of the future, how can we proceed? This paper draws a comparison between two apparently different fields: biology and economics. In biology, drug development is a highly inefficient and expensive process, which in the past has relied heavily on trial and error. Institutions such as pharmaceutical companies and universities are now radically changing their approach and adopting techniques from the new field of systems biology to integrate information from disparate sources and improve the development process. A similar revolution is required in economics if models are to reflect the nature of human economic activity and provide useful tools for policy makers. We outline the main foundations for a theory of systems economics.     

Opinion dynamics and wisdom under conformity

We study a dynamic model of opinion formation in social networks. In our model, boundedly rational agents update opinions by averaging over their neighbors’ expressed opinions, but may misrepresent their own opinion by conforming or counter-conforming with their neighbors. We show that an agent׳s social influence on the long-run group opinion is increasing in network centrality and decreasing in conformity. Concerning efficiency of information aggregation or “wisdom” of the society, it turns out that misrepresentation of opinions need not undermine wisdom, but may even enhance it. Given the network, we provide the optimal distribution of conformity levels in the society and show which agents should be more conforming in order to increase wisdom.     

关于3G业务未来发展趋势的探析

本文首先对3G业务未来发展趋势进行分析,并对3G业务平台的具体建设细节进行研究,结合国外建设的成功经验,提出自己的一些见解。