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

linear learning in changing environments abstract the decision maker receives signals imperfectly correlated with an unobservable state variable and must take actions whose payoffs depend on the state the state randomly changes over time in this environment we examine the performance of simple linear updating rules relative to bayesian learning we show that a range of parameters exists for which linear learning results in exactly the same decisions as bayesian learning although not in the same beliefs outside this parameter range we use simulations to demonstrate that the consumption level attainable under the optimal linear rule is virtually indistinguishable from the one attainable under bayes rule although the respective decisions will not always be identical these results suggest that simple rules of thumb can have an advantage over bayesian updating when more complex calculations are more costly to perform than less complex ones we demonstrate the implications of such an advantage in an evolutionary model where agents learn to learn

revised feed in tariff for solar photovoltaic in the united kingdom a cloudy future ahead abstract the united kingdom uk started implementing a national feed in tariff fit mechanism on the 1 april 2010 which included specific payment tariffs for solar photovoltaic pv installations however a revised fit rate has been put in place starting from 1 april 2012 applicable to any installations with an eligibility date of on or after 3 march 2012 this paper presents first an overview of solar pv installation in the uk this followed by a general concept of the fit in the uk before analyzing the financial impact of the new fit rate on the consumers similar financial analysis is conducted with selected countries in europe the financial analysis investigates the total profit the average rate of return and the payback period it is found that the new fit rate generates very low profit minimum rate of return and a longer payback period suggesting a downward trend of solar pv uptake in the future

peer effects in the diffusion of solar photovoltaic panels social interaction peer effects are recognized as a potentially important factor in the diffusion of new products in the case of environmentally friendly goods or technologies both marketers and policy makers are interested in the presence of causal peer effects as social spillovers can be used to expedite adoption we provide a methodology for the simple straightforward identification of peer effects with sufficiently rich data avoiding the biases that occur with traditional fixed effects estimation when using the past installed base of consumers in the reference group we study the diffusion of solar photovoltaic panels in california and find that at the average number of owner occupied homes in a zip code an additional installation increases the probability of an adoption in the zip code by 0 78 percentage points our results provide valuable guidance to marketers designing strategies to increase referrals and reduce customer acquisition costs they also provide insights into the diffusion process of environmentally friendly technologies

the stability of macroeconomic systems with bayesian learners we study abstract macroeconomic systems in which expectations play an important role consistent with the recent literature on recursive learning and expectations we replace the agents in the economy with econometricians unlike the recursive learning literature however the econometricians in the analysis here are bayesian learners we are interested in the extent to which expectational stability remains the key concept in the bayesian environment we isolate conditions under which versions of expectational stability conditions govern the stability of these systems just as in the standard case of recursive learning we conclude that bayesian learning schemes while they are more sophisticated do not alter the essential expectational stability findings in the literature

geographies of energy transition space place and the low carbon economy this paper makes a case for examining energy transition as a geographical process involving the reconfiguration of current patterns and scales of economic and social activity the paper draws on a seminar series on the geographies of energy transition security climate governance hosted by the authors between 2009 and 2011 which initiated a dialogue between energy studies and the discipline of human geography focussing on the uk government s policy for a low carbon transition the paper provides a conceptual language with which to describe and assess the geographical implications of a transition towards low carbon energy six concepts are introduced and explained location landscape territoriality spatial differentiation scaling and spatial embeddedness examples illustrate how the geographies of a future low carbon economy are not yet determined and that a range of divergent and contending potential geographical futures are in play more attention to the spaces and places that transition to a low carbon economy will produce can help better understand what living in a low carbon economy will be like it also provides a way to help evaluate the choices and pathways available

regional distribution of photovoltaic deployment in the uk and its determinants a spatial econometric approach abstract photovoltaic pv panels offer significant potential for contributing to the uk s energy policy goals relating to decarbonisation of the energy system security of supply and affordability the substantive drop in the cost of panels since 2007 coupled with the introduction of the feed in tariff fit scheme in 2010 has resulted in a rapid increase in installation of pv panels in the uk from 26 5mwp in 2009 to over 5gw by the end of 2014 yet there has been no comprehensive analysis of the determinants of pv deployment in the uk this paper addresses this gap by employing spatial econometrics methods to a recently available data set at a fine geographical detail following a traditional regression analysis a general to specific approach has been adopted where spatial variations in the relationships have been examined utilising the spatial durbin model using the cross sectional data relating to the uk nuts level 3 data empirical results indicate that demand for electricity population density pollution levels education level of households and housing types are among the factors that affect pv uptake in a region moreover lagrange multiplier test results indicate that the spatial durbin model may be properly applied to describe the pv uptake relationship in the uk as there are significant regional spillover effects

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

central bank misperceptions and the role of money in interest rate rules research with keynesian style models has emphasized the importance of the output gap for policies aimed at controlling inflation while declaring monetary aggregates largely irrelevant critics however have argued that these models need to be modified to account for observed money growth and inflation trends and that monetary trends may serve as a useful cross check for monetary policy we identify an important source of monetary trends in form of persistent central bank misperceptions regarding potential output simulations with historical output gap estimates indicate that such misperceptions may induce persistent errors in monetary policy and sustained trends in money growth and inflation if interest rate prescriptions derived from keynesian style models are augmented with a cross check against money based estimates of trend inflation inflation control is improved substantially

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

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

photovoltaic power stations in germany and the united states a comparative study by data envelopment analysis abstract this study compares photovoltaic pv power stations between germany and the united states to examine which country more efficiently provides renewable energy in their usages for the comparative analysis this study utilizes data envelopment analysis dea as a methodology to evaluate the performance of pv power stations from the perspective of both solar and land usages a total of one hundred sixty pv power stations eighty in germany and eighty in the united states are used for this comparison the demand for sustainable energy and energy security has been rapidly increasing over the past decade because of concerns about environment and limited resources pv solutions are one of many renewable technologies that are being developed to satisfy a recent demand of electricity germany is the world s top installer and consumer of pv power and the united states is one of the top five nations germany leads the way in installed pv capacity even though the nation has less solar resources and land area due to limited solar resources low insolation and sunshine and land area the united states should have a clear advantage over germany however the empirical result of this study exhibits that pv power stations in germany operate more efficiently than those of the united states even if the latter has many solar and land advantages the surprising result indicates that the united states has room for improvement when it comes to utilizing solar and land resources and needs to reform the solar policy for such a purpose feed in tariff fit may be an effective energy policy at the state level in the united states because the fit provides investors such as utility companies and other types of energy firms with financial incentives to develop large pv power stations and generation facilities for other renewable energy it may be true that the fit is a powerful policy tool to promote pv and other renewable installation and support a reduction of an amount of greenhouse gases however the fit poses a large financial burden to consumers with a massive increase in renewable energy installation like in germany and spain therefore it is necessary for the united states to consider how to align a policy with a speed of technology innovation to balance between the benefit and the cost derived from the policy implementation on renewable energy in addition this study discusses policy issues regarding cost allocation due to fit among stakeholders related to the electric power industry at the end this study proposes a new type of wholesale electricity market that provides simultaneous trading on electricity and greenhouse gas emissions by fully utilizing modern computer science technology that exists in universities and national laboratories of the united states

inflation variability and gradualist monetary policy this paper considers the optimal approach to reducing inflation when the cost of inflation is its conditional variability inflation is stochastically related to money growth with unobservable time varying autonomous and induced components a sharp reduction in money growth provides information about the responsiveness of inflation to money but also induces variability as the economy heads into unknown territory gradual policy is always optimal and the model explains why moderate inflation countries adopt a much more gradual money growth reduction than high inflation countries additionally the analysis sheds light on the more general problem of learning with two unobservable parameters

exploring domestic energy saving the role of environmental concern and background variables abstract the main purpose of this paper is to investigate whether residents environmental concern has any effect on their energy saving curtailments and efficiency investments the novelty of the present work lies in the fact that it seeks to investigate this topic in a multi country setting exploiting data from nine oecd countries australia canada czech republic france italy south korea netherlands norway and sweden and also in that it employs a latent variable model which allows us to examine the conditions necessary for the results to be comparable across different countries novel in this paper is also the focus on the role of environmental concern as a factor of several curtailments and efficiency investments our results suggest that people with higher environmental concern are on average more likely to perform energy saving curtailments and also are more likely to have some energy efficiency retrofits installed in dwellings most of the socio economic and demographic variables have mixed effects on efficiency investments and curtailments however some interesting patterns emerged with respect to the age of respondents household income education and gender of respondents and also the size of household

a value function arising in the economics of information abstract the value function for a problem in the economics of the optimal accumulation of information is calculated as a fixed point of a contraction mapping by direct numerical iteration the optimal policy function is obtained as is the function defined as the sum of current expected reward and the discounted expected value of following the optimal policy in the future the optimal policy function is shown to be sensitive to the discount factor indeed for large values of the discount factor weighting the future heavily the policy function has a break and the value function is apparently not differentiable

managing disinflation under uncertainty in this paper we analyze disinflation policy when a central bank has imperfect information about private sector inflation expectations but learns about them from economic outcomes which are in part the result of the disinflation policy itself the form of uncertainty is manifested as uncertainty about the effect of past disinflation policy on the current output gap this differs from other studies on learning and control in a monetary policy context e g ellison 2006 svensson and williams 2007 that assume uncertainty about the effects of current policy actions on the economy we derive the central bank s optimal disinflation strategy under active learning dop and compare it with two limiting cases certainty equivalence policy cep or passive learning and a brainard style cautionary monetary policy cp it turns out that under the dop inflation stays between the levels implied by the cep and the cp a novel result e g unlike beck and wieland 2002 is that this holds irrespective of the initial level of inflation at high levels of inherited inflation the dop moves closer to the cep at low levels of inherited inflation the dop resembles the cp

actively learning by pricing a model of an experimenting seller this article presents a model of a rational seller who is actively learning the slope of his demand curve via his pricing strategy consequently this seller optimally experiments with his price resulting price patterns show a tendency for discreteness as observed in the data which has proved to be a major challenge to most price setting models the experimentation motive can also replicate the observation that prices are more volatile than costs as well as the presence of many idiosyncratic price changes in the data it can do so without a need to assume the existence of large idiosyncratic shocks

consumer attitudes towards domestic solar power systems the success of the uk policy to reduce carbon emissions is partly dependent on the ability to persuade householders to become more energy efficient and to encourage installation of domestic solar systems solar power is an innovation in the uk but the current policy of stimulating the market with grants is not resulting in widespread adoption this case study using householders in central england investigates householder attitudes towards characteristics of solar systems and identifies some of the barriers to adoption the study utilises diffusion of innovations theory to identify attitudes towards system attributes and isolates the characteristics that are preventing a pragmatic early majority from adopting the technology a group of early adopters and a group of assumed early majority adopters of solar power were surveyed and the results show that overall although the early majority demonstrate a positive perception of the environmental characteristics of solar power its financial economic and aesthetic characteristics are limiting adoption differences exist between the two groups showing support for the concept of a chasm between adopter categories after moore crossing the chasm marketing and selling high tech products to mainstream customers second ed harper perennial new york however if consumers cannot identify the relative advantage of solar power over their current sources of power which is supplied readily and cheaply through a mains system it is unlikely that adoption will follow recommendations concerning the marketing and development of solar products are identified

the market value of variable renewables the effect of solar wind power variability on their relative price this paper provides a comprehensive discussion of the market value of variable renewable energy vre the inherent variability of wind speeds and solar radiation affects the price that vre generators receive on the market market value during windy and sunny times the additional electricity supply reduces the prices because the drop is larger with more installed capacity the market value of vre falls with higher penetration rate this study aims to develop a better understanding on how the market value with penetration and how policies and prices affect the market value quantitative evidence is derived from a review of published studies regression analysis of market data and the calibrated model of the european electricity market emma we find the value of wind power to fall from 110 of the average power price to 50 80 as wind penetration increases from zero to 30 of total electricity consumption for solar power similarly low value levels are reached already at 15 penetration hence competitive large scale renewable deployment will be more difficult to accomplish than as many anticipate

robustness and u s monetary policy experimentation we study how a concern for robustness modifies a policy maker s incentive to experiment a policy maker has a prior over two submodels of inflationunemployment dynamics one submodel implies an exploitable trade off the other does not bayes law gives the policy maker an incentive to experiment the policy maker fears that both submodels and his prior probability distribution over them are misspecified we compute decision rules that are robust to misspecifications of each submodel and of the prior distribution over submodels we compare robust rules to ones that cogley colacito and sargent 2007 computed assuming that the models and the prior distribution are correctly specified we explain how the policy maker s desires to protect against misspecifications of the submodels on the one hand and misspecifications of the prior over them on the other have different effects on the decision rule

experimentation with accumulation abstract we study signal dependent experimentation in the presence of accumulation and show that the passive learner s action surprisingly coincides with the experimentor s when the unknown term is the one determining the decay rate of the stock while they differ when the parameter being learned is the one measuring the accumulation rate these results highlight the importance of the dynamic structure of the problem in signal dependent experimentation moreover they have important consequences for the pollution accumulation debate currently in progress

benefits from u s monetary policy experimentation in the days of samuelson and solow and lucas a policy maker knows two models of ination unemplo yment dynamics one implies an exploitable trade o the other does not the policy maker s prior probability over the two models is part of his state vector bayes law converts the prior probability into a posterior probability at each date and gives the policy maker an incentive to experiment for two models calibrated to u s data through the early 1960s we isolate the component of government policy that is due to experimentation by comparing the outcomes from two bellman equations the rst of which experiments and learns the second of which learns but doesn t experiment we interpret the second as an anticipated utility model and study how well its outcomes approximate those from the experiment and learn bellman equation the approximation is good for our calibrations the benets from purposeful experimentation are small

it s the economy and then some modeling the presidential vote with state panel data using data for the 50 us states for presidential elections from 1972 to 2004 two theories for determining state voting outcomes are considered jointly the economy matters and home grown ness theories fixed effects regressions show that measures of the economy matters real income unemployment and a proxy for inflation have the predicted effects on state voting patterns for presidential elections the home grown theory receives mixed support there is weak evidence that incumbent party candidates garner greater support in their home states there is strong support however for the proposition that incumbent party candidates fare worse in the home state of rival party candidates

active learning monte carlo results abstract the revival of interest in learning in stochastic control models invites the examination of some unanswered issues from earlier work following in the tradition of prescott and macrae we consider active learning to examine the question of when these methods are superior to passive learning in the earlier literature it was not possible to address this question because computer speeds were not great enough however modern supercomputers make it possible to reopen this issue in this paper we will examine two well known stochastic control models the macrae model and the abel model although no general conclusions can be drawn the results from the macrae model and the abel model indicate that in certain cases active learning may be superior to passive learning and certainty equivalence in the almost all cases we have analyzed so far active learning is superior to passive learning which in turn is superior to certainty equivalence

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 role of model uncertainty and learning in the u s postwar policy response to oil prices abstract this paper studies optimal monetary policy in a framework that explicitly accounts for policymakers uncertainty about the channels of transmission of oil prices into the economy more specifically using postwar us data i examine the evolution of the policy recommendations originating from an optimal linear regulator problem that encompasses model uncertainty and learning as proposed by cogley and sargent 2005b in this environment i find that one of the underlying models dominates the robust interest rate response to oil prices and i show that this result is due to the instability of this specification in the sample period under analysis