learning and control in a changing economic environment abstract in this paper we investigate optimal bayesian learning and control with lagged dependent variables and time varying unknown parameters we assess both the performance of alternative decision rules as in the computationally oriented dual control literature as well as the dynamics of learning and convergence of beliefs as in the more theoretically oriented bayesian learning literature our numerical results indicate that the optimal decision rule involves a noticeable degree of experimentation for moderate to large levels of uncertainty in most situations though the optimal rule will remain less activist than a certainty equivalent rule and induce gradualism exceptions occur when the process to be controlled is near the deterministic steady state in this situation we find that the decision maker will repeatedly undertake costly experiments the extent of optimal experimentation is lower if the unknown parameter is perceived to vary over time in contrast to the fixed parameter case however parameter uncertainty is continually renewed and the incentive to experiment never ceases

active learning and optimal climate policy this paper develops a climate economy model with uncertainty irreversibility and active learning whereas previous papers assume learning from one observation per period or experiment with control variables to gain additional information this paper considers active learning from investment in monitoring specifically in improved observations of the global mean temperature we find that the decision maker invests a significant amount of money in climate research far more than the current level in order to increase the rate of learning about climate change this helps the decision maker make improved decisions the level of uncertainty decreases more rapidly in the active learning model than in the passive learning model with only temperature observations as the uncertainty about climate change is smaller active learning reduces the optimal carbon tax the greater the risk the larger is the effect of learning the method proposed here is applicable to any dynamic control problem where the quality of monitoring is a choice variable for instance the precision at which we observe gdp unemployment or the quality of education

global warming irreversibility and learning a number of economists have argued that the literature on the irreversibility effect implies that current abatement of greenhouse gas emissions should be greater when there is the possibility of obtaining better information in the future about the potential damages from global warming than when there is no possibility of obtaining better information in this paper we show that even the simplest model of global warming does not satisfy either of epstein s 1980 sufficient conditions so it is not possible to use epstein s analysis to tell whether the irreversibility effect applies to models of global warming we derive an alternative sufficient condition for the irreversibility effect to hold

the impact and targeting of social infrastructure investments lessons from the nicaraguan social fund this brief summarizes the impact and targeting of social infrastructure investments lessons from the nicaraguan social fund the fund was created in 1990 the benefit incidence and impact of projects financed by the nicaraguan emergency social investment fund are investigated using a sample of beneficiaries a national household survey and two distinct comparison groups the first group is constructed on the basis of geographic proximity between similar facilities and their corresponding communities the second is drawn from the national living standards measurement study survey sample using propensity score matching techniques the analysis finds that the social fund investments in latrines schools and health posts are targeted to poor communities and households whereas those in sewerage are targeted to the better off investments in water systems are poverty neutral education investments have a positive significant impact on school outcomes regardless of the comparison group the analysis finds that use of health investments is less clear using one comparison group the analysis finds that use of health clinics increased as a result of the investments using both it finds higher use of clinics for children under age six with diarrhea with neither comparison group does it find improvements in health outcomes social fund investments in water and sanitation improve access to services but have no effect on health outcomes

how important is pro social behaviour in the delivery of public services a number of papers have suggested that pro social behaviour in the workplace may be sensitive to the institutional environment but there is little empirical research that attempts to test this directly using data on worker behaviour this is the aim of this paper we show that individuals in the non profit sector are significantly more likely to do unpaid overtime than those in the for profit sector however we find no evidence of adjustment along either the extensive or intensive margins when individuals change sectors the results of our analysis therefore point to selection and we find supporting evidence that individuals do self select on the basis of their propensity to donate labour

optimal learning on climate change why climate skeptics should reduce emissions climate skeptics typically argue that the possibility that global warming is exogenous implies that we should not take additional action towards reducing emissions until we know what drives warming this paper however shows that even climate skeptics have an incentive to reduce emissions such a directional change generates information on the causes of global warming since the optimal policy depends upon these causes they are valuable to know although increasing emissions would also generate information that option is inferior due its irreversibility we show that optimality can even imply that climate skeptics should actually argue for lower emissions than believers

climate change and optimal energy technology r d policy public policy response to global climate change presents a classic problem of decision making under uncertainty theoretical work has shown that explicitly accounting for uncertainty and learning in climate change can have a large impact on optimal policy especially technology policy however theory also shows that the specific impacts of uncertainty are ambiguous in this paper we provide a framework that combines economics and decision analysis to implement probabilistic data on energy technology research and development r d policy in response to global climate change we find that given a budget constraint the composition of the optimal r d portfolio is highly diversified and robust to risk in climate damages the overall optimal investment into technical change however does depend in a non monotonic way on the risk in climate damages finally we show that in order to properly value r d abatement must be included as a recourse decision

matching the gold standard comparing experimental and nonexperimental evaluation techniques for a geographically targeted program abstract we compare nonexperimental impact estimates based on matching methods with those from a randomized evaluation to determine whether the nonexperimental approach can match the so called gold standard the social experiment we use was carried out to evaluate a geographically targeted conditional cash transfer antipoverty program in nicaragua the outcomes we assess include several components of household expenditure and a variety of children s health outcomes including breast feeding vaccinations and morbidity we find that using each of the following improves performance of matching for these outcomes 1 geographically proximate comparison samples 2 stringent common support requirements and 3 both geographic and household level matching variables even for a geographically targeted program in which the selection is at the geographic rather than at the individual or household level and in which it is not possible to find comparison individuals or households in the program locales m

fundamental irreversibilities in stock externalities abstract this paper concerns the irreversibility effect in stock externalities in an environment of uncertainty with learning taking place one may wish to under emit today to avoid potential environmental irreversibilities alternatively one may wish to under invest in pollution control capital avoiding investments in sunk capital that turn out to be wasted the paper develops theoretical results on the tension between these two effects and separates risk aversion from the irreversibility effect the paper also presents a simple example in climate change policy

poverty and household size the widely held view that larger families tend to be poorer in developing countries has influenced research and policy the scope for size economies in consumption cautions against this view we find that the correlation between poverty and size vanishes in pakistan when the size elasticity of the cost of living is about 0 6 this turns out to be the elasticity implied by a modified version of the food share method of setting scales by contrast some measures of child nutritional status indicate an elasticity of unity consideration of the weight attached to child versus adult welfare may help resolve the non robustness of demographic profiles of poverty excerpt

regulation with anticipated learning about environmental damages a regulator anticipates learning about the relation between environmental stocks and economic damages for a model with linear quadratic abatement costs and environmental damages and a general learning process we show analytically that anticipated learning decreases the optimal level of abatement at a given information set if learning causes the regulator to eventually decide that damages are higher than previously thought learning eventually increases abatement learning also favors the use of taxes rather than quotas using a model that is calibrated to describe the problem of global warming we show numerically that anticipated learning causes a significant reduction in first period abatement and a small increase in the preference for taxes rather than quotas even if the regulator s initial priors about environmental damages are much too optimistic he is able to learn quickly enough to keep the expected stock trajectory near the optimal trajectory

stochastic control for economic models past present and the paths ahead abstract on the 30th anniversary of a meeting between engineers and economists at princeton university to discuss the potential application of stochastic control methods to economics this paper provides a review of past present and paths ahead the events surrounding some of the key developments of the past are described along with a discussion of the present state of the research and of paths for future research the paper is structured around the primary methods for solving quadratic linear economic stochastic control models namely open loop classical control handcrafted feedback rules optimal feedback min max control optimal feedback rules with parameter uncertainty and dual control the paper also includes a discussion of software developments in economic stochastic control modeling

infrastructural investment in long run economic growth south africa 1875 2001 summary productive public expenditure in the area of infrastructure such as roads transportation and housing can play an important role in promoting economic growth and encouraging private investment developments in endogenous growth theory introduce the possibility of a productive role for public expenditure this paper seeks to explain the relationship between investment in economic infrastructure and long run economic growth by examining the experience of south africa in a time series context the main findings that emerge from our examination of economic growth and economic infrastructure in south africa may be summarized as follows investment in infrastructure does appear to lead economic growth in south africa and does so both directly and indirectly the latter by raising the marginal productivity of capital there is weak evidence of feedback from output to infrastructure while the finding of an infrastructure growth impact is robust

caution and probing in a macroeconomic model abstract this paper reports on the application of an adaptive dual control technique to a small macroeconometric model of the u s economy both monetary and fiscal policy variables are used in the model the experiments find that probing and active learning will occur in small macroeconometric models but that unrealistically high terminal period penalties on state deviations are required before it appears

supporting communities in transition the impact of the armenian social investment fund the armenian social investment fund supports communities efforts to improve local infrastructure during armenia s economic transition away from central planning financing community designed and implemented projects to rehabilitate primary schools water systems and other infrastructure this article considers the targeting household impact and community effects of the social fund s activities it relies on a nationally representative household survey oversampled in areas where the social fund was active using propensity and pipeline matching techniques to control for community self selection into the social fund it evaluates the household effects of rehabilitating schools and water systems the results show that the social fund reached poor households particularly in rural areas education projects increased households spending on education significantly and had mild effects on school attendance potable water projects increased household access to water and had mild positive effects on health communities that completed a social fund project were less likely than the comparison group to complete other local infrastructure projects suggesting that social capital was expended in these early projects by contrast communities that joined the social fund later and had not yet completed their projects took more initiatives not supported by the social fund in centrally planned economies national governments exerted tremendous economic control this control extended to investment in local infrastructure including building and maintaining roads schools and water systems when these economies collapsed governments became bereft of resources systems for maintaining local infrastructure began to fail as deep economic recession took hold schools and water systems fell into disrepair local public services deteriorated compounding other hardships for people living in postcommunist conditions but because communities were accustomed to relying on central authorities to meet local needs they often were unable to address their problems

community based development and poverty alleviation an evaluation of china s poor village investment program we conduct the first systematic evaluation of the world s largest community based development program china s flagship poverty alleviation program began in 2001 which finances public investments in designated poor villages based on participatory village planning we use matching methods and a panel household and village data set with national coverage to compare changes from 2001 to 2004 in designated poor villages that began plan investments and in designated poor villages that had yet to begin plan investments we find that the program significantly increased both government and village financed investments while the program did not increase the income or consumption of poorer households it did increase the income and consumption of richer households by 6 1 to 9 2 we also find suggestive evidence that governance matters in the distribution of program benefits relative gains were greater for richer households in villages with more educated leaders and higher quality village committees delivered greater benefits to both richer and poorer households

local inequality and project choice theory and evidence from ecuador this paper provides evidence consistent with elite capture of social fund investment projects in ecuador exploiting a unique combination of data sets on village level income distributions social fund project administration and province level electoral results we test a simple model of project choice when local political power is unequally distributed in accordance with the predictions of the model poorer villages are more likely to receive projects that provide excludable private goods to the poor such as latrines controlling for poverty more unequal communities are less likely to receive such projects consistent with the hypothesis of elite capture these results are sensitive to the specific measures of inequality and elite power used in the empirical analysis and are strongest for expenditure shares at the top of the distribution

learning experimentation and monetary policy abstract we present a model of monetary policy where the policymaker faces uncertainty about which he is learning in a bayesian fashion a fixed money supply rule is not optimal since the learning leads to adjustments in the monetary action we present cases in which it is optimal to bear some cost in terms of current output performance in order to gain information that can be used in the formulation of future monetary policy experimentation therefore pays we also show that even passive learning without experimentation still leads to an activist monetary policy i e one that is responsive to new information

climate policy under fat tailed risk an application of dice uncertainty plays a significant role in evaluating climate policy and fat tailed uncertainty may dominate policy advice should we make our utmost effort to prevent the arbitrarily large impacts of climate change under deep uncertainty in order to answer to this question we propose a new way of investigating the impact of fat tailed uncertainty on optimal climate policy the curvature of the optimal carbon tax against the uncertainty we find that the optimal carbon tax increases as the uncertainty about climate sensitivity increases but it does not accelerate as implied by weitzman s dismal theorem we find the same result in a wide variety of sensitivity analyses these results emphasize the importance of balancing the costs of climate change against its benefits also under deep uncertainty 2013 springer science business media dordrecht

learning and stock effects in environmental regulation the case of greenhouse gas emissions abstract this paper concerns the optimal regulation of greenhouse gases that lead to global climate change in particular we focus on uncertainty and learning which over time resolves uncertainty we present an empirical stochastic model of climate economy interactions and present results on the tension between postponing control until more is known vs acting now before irreversible climate change takes place uncertainty in our model is in the damage caused by global warming the results suggest that a temporary carbon tax may dominate a permanent one because a temporary tax may induce increased flexibility

the social impact of social funds in jamaica a participatory econometric analysis of targeting collective action and participation in community driven development qualitative data from a case study of the jamaica social investment fund reveal that the social fund process is elite driven and decision making tends to be dominated by a small group of motivated individuals however there is broad based satisfaction with the outcome quantitative data from 500 households mirror these findings by showing that ex ante the social fund does not address the expressed needs of the majority of individuals in the majority of communities by the completion of the project however 80 per cent of the community expresses satisfaction with the outcome an analysis of the determinants of participation reveals that better educated and better networked individuals dominate the process propensity score analysis demonstrates that jsif has had a causal impact on improvements in trust and the capacity for collective action but these gains are greater for elites

cost benefit analysis under uncertainty a note on weitzman s dismal theorem abstract weitzman s 2009 famous dismal theorem argues that fat tails in the distribution of warming may pose problems for cost benefit analysis as it may imply that society might be willing to exchange today s consumption for future consumption at an infinite rate his analysis is based on the stochastic discount factor we show that in situations in which the stochastic discount factor is applicable it is optimal for society to devote only a finite amount of resources to protect against climate change for general assumptions on the investment returns cost benefit analysis must consider the joint distribution of the marginal utility of future consumption and marginal returns to investment in the different future states of nature we explore the range of situations under which challenges for applying cost benefit analysis under uncertainty remain

uncertainty learning and heterogeneity in international environmental agreements this paper concerns the formation of international environmental agreements under uncertainty about environmental damage with different models of learning complete learning partial learning or no learning the results of the existing literature are generally pessimistic the possibility of either complete or partial learning generally reduces the level of global welfare that can be achieved from forming an iea relative to no learning that literature regards uncertainty as a parameter common to all countries so that countries are identical ex ante as well as ex post in this paper we extend the literature to the case where there is no correlation between damage costs across countries each country is uncertain about a particular parameter in our case the benefit cost ratio drawn from a common distribution but ex post each country s realized parameter value is independently drawn consequently while countries remain identical ex ante they may be heterogeneous ex post we show that this change reinforces the negative conclusions about the effects of partial learning on international environmental agreements but under certain conditions moderates the negative conclusions about the effects of complete learning

rural electrification and employment in poor countries evidence from nicaragua summary this paper shows that rural electrification is associated with big changes in the time use of men and women in nicaragua even in the absence of labor saving appliances electricity is shown to increase the propensity of rural nicaraguan women to work outside the home by about 23 but to have no impact on male employment these findings suggest significant potential benefits to rural electrification that are not generally captured in cost benefit analyses such as greater women s earnings and reduced deforestation

buying greenhouse insurance the economic costs of carbon dioxide emission limits in recent years a growing concern that the increasing accumulation of greenhouse gases will lead to undesirable changes in global climate has resulted in a number of proposals both in the united states and internationally to set physical targets for reducing greenhouse gas emissions but what will these proposals cost based on the authors earlier ground breaking work buying greenhouse insurance outlines a way to think about greenhouse effect decisions under uncertainty it describes an insightful model for determining the economic costs of limiting carbon dioxide emissions produced by burning fossil fuels and provides a solid analytical base for rethinking public policy on the farreaching issue of global warming manne and richels present region by region estimates of the costs that would underlie an international agreement using a computer model known as global 2100 they analyze the economic impacts of limiting c02 emissions under alternative supply and conservation scenarios the results clearly indicate that a reduction in emissions is not the sole policy response to potential climate change following a summary of the greenhouse effect its likely causes and possible consequences manne and richels take up issues that concern the public at large they provide an overview of global 2100 look at how the u s energy sector is likely to evolve under businessas usual conditions and under carbon constraints and describe the concept of greenhouse insurance they consider possible global agreements including an estimate of benefits that might result from trading in an international market in emission rights they conclude with a technical description directed toward modeling specialists alan manne is professor of operations research at stanford university richard richels is director of the energy analysis and planning department at the electric power research institute

scientific progress and irreversibility an economic interpretation of the precautionary principle abstract we consider the problem of the optimal use of a good whose consumption can produce damages in the future scientific progress is made over time that provides information on the distribution of the intensity of damages we show that this progress induces earlier prevention effort only if prudence is larger than twice absolute risk aversion this paper thus identifies the class of quite restrictive but plausible conditions such that scientific uncertainties justify an immediate reduction of the consumption of a potentially toxic substance

bayesian learning growth and pollution abstract environmental problems such as climate change have great uncertainties current expectations are that uncertainties about climate change will be resolved quickly we examine this hypothesis theoretically and computationally we consider bayesian learning about the relationship between greenhouse gas levels and global mean temperature changes a key uncertainty learning is non trivial because of a stochastic shock to the realized temperature we find theoretically the expected learning time which is related to the variance of the shock and the emissions policy implying a tradeoff between the benefits of controlling emissions and information we imbed the learning model into an optimal growth model with a climate sector and solve the resulting dynamic program we find computationally that learning takes on average over 90 yr far longer than currently believed

learning by doing and the value of optimal experimentation abstract recent research on learning by doing has provided the limit properties of beliefs and actions for a class of learning problems in which experimentation is an important aspect of optimal decision making however under these conditions the optimal policy cannot be derived analytically because bayesian learning about unknown parameters introduces a nonlinearity in the dynamic optimization problem this paper utilizes numerical methods to characterize the optimal policy function for a learning by doing problem that is general enough for practical economic applications the optimal policy is found to incorporate a substantial degree of experimentation under a wide range of initial beliefs about the unknown parameters dynamic simulations indicate that optimal experimentation dramatically improves the speed of learning and the stream of future payoffs furthermore these simulations reveal that a policy which separates control and estimation and does not incorporate experimentation frequently induces a long lasting bias in the control and target variables while these sequences tend to converge steadily under the optimal policy they frequently exhibit non stationary behavior when estimation and control are treated separately

the climate change learning curve abstract the purpose of this paper is to confront economic models of climate change with the reality that limited information exists with which to form expectations about the evolution of the climate a key element in the tension between those who believe we should impose aggressive climate change mitigation policies and those who do not is the question of if we are merely in a long period of shock induced above average temperatures or if observed increases in temperature are a result of carbon emissions this paper characterizes learning dynamics resulting from the use of observations of temperature to update beliefs about two key characteristics of global climate the persistence of natural trends and the sensitivity of temperature to atmospheric carbon levels this paper shows that contrary to predictions in the literature that uncertainty may be resolved very quickly the time to learn the true processes may be in the order of thousands of years further this paper shows the effects of uncertainty on the likelihood that observations from the statistical record lead to important estimate and policy errors

on modeling and interpreting the economics of catastrophic climate change with climate change as prototype example this paper analyzes the implications of structural uncertainty for the economics of low probability high impact catastrophes even when updated by bayesian learning uncertain structural parameters induce a critical tail fattening of posterior predictive distributions such fattened tails have strong im plications for situations like climate change where a catastrophe is theoretically possible because prior knowledge cannot place sufficiently narrow bounds on overall damages this paper shows that the economic consequences of fat tailed structural uncertainty along with unsureness about high temperature damages can readily outweigh the effects of discounting in climate change policy analysis