Uncertainty,story-telling and transformative learning: An instructor’s experience of TEFI’s Walking Workshop in Nepal

ABSTRACT

This article recounts three stories from TEFI’s walking workshop in Nepal: the construction of a road through what was once a trekking path; a dance-floor encounter at a Himalayan party; and the arrival of one participant, fatigued by jet lag and disoriented by the new surroundings. These stories of confusion, discomfort and fear are linked by one common theme: the potential of uncertainty to foster deep reflection and nuanced conclusions. The premise that uncertainty is to be valued and even cultivated has been explored in educational theory, spiritual traditions, and research on transformative learning. These sources affirm the role of uncertainty in the process of knowledge creation. However, accepting this role can be challenging for educators because it requires they assume a new identity, one which they may perceive as being at odds with their status as “teacher” the identity of learner. One way for the educator to address this challenge may be through recounting their own stories of uncertainty. Stories of being immersed in unfamiliar situations that challenge, confuse and even frighten – stories, in other words of being a tourist – can foster reflection on an intellectual, emotional and spiritual level, engaging the “whole” person, and thus initiating the educator/learner’s transformative journey.     

Uncertainty Associated with Future Environmental Costs and the Market's Differential Response to Earnings Information

This study examines whether the uncertainty arising from a firm's exposure to future environmental costs (environmental uncertainty) affects the market's price sensitivity to reported earnings. Specifically, when environmental uncertainty is significantly high, are investors more responsive to reported earnings released by 'high-polluting' firms than reported earnings announced by 'low-polluting' firms within the same industry? The initial impact of Title IV (the acid rain provisions) of the 1990 Clean Air Act Amendments (1990 CAAA) on the US electric utility industry provides the research setting required to isolate the effects of environmental uncertainty while addressing this question. Consistent with theoretical predictions, we find that the earnings response coefficients (ERCs) of high-polluting electric utilities are significantly greater than those of their low-polluting counterparts during a predicted period of elevated environmental uncertainty. In adjoining sample years associated with lower environmental uncertainty, we observe no statistical difference in the magnitude of the ERCs between these two groups. In addition, the study's findings suggest that the magnitude of the ERC is increasing in the firm's exposure to future environmental costs, after controlling for other factors that potentially affect ERCs.     

Additive and Multiplicative Uncertainty Revisited: What Explains the Contrasting Biases?

above the certainty level while for additive uncertainty the price should be lower than the certainty level. This note gives an intuitive explanation for the result after first presenting a parsimonious review of the two models. We also discuss which, if either, of the two models is more realistic. Received December 14, 2001; revised version received July 16, 2002 Published online: April 30, 2003 We thank referees for helpful comments. Ciaran Driver would like to acknowledge the research facilities from ANU, Canberra for their help in writing this paper.     

CROSS‐DOCKING AND ITS IMPLICATIONS IN LOCATION‐DISTRIBUTION SYSTEMS

Cross‐docking replaces traditional warehousing, enabling continuous flow of items without storage. Here we model location‐distribution networks, that include cross‐docking facilities, to obtain the latter's impact on the supply chain. We formulate optimization models to minimize total cost in three multi‐echelon networks, each model generalizing the preceding one. The first includes a single manufacturer, one product type, and multiple customers. Cross‐docks are to be located between origin and destinations. Besides solving optimally, a tool for quantitative analysis of direct‐shipment decisions is developed. The second model considers more than one product: We determine a cost‐effective sequence of items for indirect shipment (via cross‐docks). Finally, in a network with multiple origins, optimal solutions are obtained for 40 medium‐sized and larger examples.     

采取网络型的政府市场供给模式应对房价问题

面对不断飙升的房价,从理论界到政策层面对其原因都有不同的解读,但从实践结果来看对房价的治理并不理想。本文在综合分析理论研究与国家调控政策的基础上,认为创新措施采取网络型的政府市场供给模式是解决房价过快上涨的有效途径。文章着重对这一模式进行了分析,并认为此举对缓解供需矛盾、解决市场的信息不对称、市场操控、改变预期、稳定房价等都有非常重要的作用。     

Stochastic Technology, Risk Preferences, and Adoption of Site-Specific Technologies

A model of farmer decision making is developed to determine the extent to which uncertainties about soil fertility and weather affect the value of site-specific technologies (SSTs) using jointly estimated risk and technology parameters. Uncertainty can lead risk-averse farmers to apply more fertilizers and generate more pollution than in the certainty case. Ignoring uncertainty and risk aversion would overestimate the economic and environmental benefits of SSTs and underestimate the subsidy required to induce adoption. Accounting for uncertainties and risk preferences might explain the low observed adoption rates of SSTs. Improving the accuracy of SSTs would increase the incentives for adoption.     

Forecasting economic time series using flexible versus fixed specification and linear versus nonlinear econometric models

Nine macroeconomic variables are forecast in a real-time scenario using a variety of flexible specification, fixed specification, linear, and nonlinear econometric models. All models are allowed to evolve through time, and our analysis focuses on model selection and performance. In the context of real-time forecasts, flexible specification models (including linear autoregressive models with exogenous variables and nonlinear artificial neural networks) appear to offer a useful and viable alternative to less flexible fixed specification linear models for a subset of the economic variables which we examine, particularly at forecast horizons greater than 1-step ahead. We speculate that one reason for this result is that the economy is evolving (rather slowly) over time. This feature cannot easily be captured by fixed specification linear models, however, and manifests itself in the form of evolving coefficient estimates. We also provide additional evidence supporting the claim that models which ‘win’ based on one model selection criterion (say a squared error measure) do not necessarily win when an alternative selection criterion is used (say a confusion rate measure), thus highlighting the importance of the particular cost function which is used by forecasters and ‘end-users’ to evaluate their models. A wide variety of different model selection criteria and statistical tests are used to illustrate our findings.     

THEORIES OF CHOICE UNDER IGNORANCE AND UNCERTAINTY

Abstract. In this paper, Knight's distinction between risk and uncertainty, and its significance for economic analysis are examined. The paper consists of a survey of some recent developments on the theory of choice under uncertainty and some applications of these theories to problems for which Bayesian Decision Theory has not proved entirely satisfactory. Two problems are examined in detail. The first is that of finance and insurance and the second is that of risktaking behaviour with special emphasis on lotteries.     

Does economic policy uncertainty drive the dynamic spillover among traditional currencies and cryptocurrencies? The role of the COVID-19 pandemic

The paper examines the dynamic spillover among traditional currencies and cryptocurrencies before and during the COVID-19 pandemic and investigates whether economic policy uncertainty (EPU) impacts this spillover. Based on the TVP-VAR approach, we find evidence of spillover effects among currencies, which increased widely during the pandemic. In addition, results suggest that almost all cryptocurrencies remain as “safe-haven” tools against market uncertainty during the COVID-19 period. Moreover, comparative analysis shows that the total connectedness for cryptocurrencies is lower than for traditional currencies during the crisis. Further analysis using quantile regression suggests that EPU exerts an impact on the total and the net spillovers with different degrees across currencies and this impact is affected by the health crisis. Our findings have important policy implications for policymakers, investors, and international traders.     

货币政策和银行风险承担：一种非线性关系

宽松的货币政策会通过估值、收入和现金流机制,追逐收益机制以及中央银行沟通和反应机制等渠道增加银行风险承担,通过风险转移机制降低银行风险承担,从而导致货币政策与银行风险承担之间可能存在复杂的非线性关系。本文使用面板阈值模型,基于我国银行业数据研究了货币政策对银行风险承担的影响,发现我国货币政策对银行风险承担的影响存在门限效应,即货币政策对银行风险承担的影响取决于货币政策基准利率偏离泰勒规则利率的程度。当这种偏离小于门限值时,宽松货币政策会增加银行风险承担;当这种偏离大于门限值时,宽松货币政策会降低银行风险承担。本文研究对更好地理解我国货币政策对银行风险承担及金融稳定的影响有一定参考意义。