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This dissertation uses Bayesian methods to understand how expectations are formed and their role in macroeconomic fluctuations. All three essays study expectations formation through different perspectives and econometric tools.The first chapter analyzes the impact of central bank transparency on the evolution of agents’ expectations for the Mexican case via a New Keynesian model with adaptive learning and survey forecasts. Among multiple scenarios, the data prefer the observed transparency degree followed by the Mexican central bank, where the central bank credibly communicatesthe inflation target and discloses relevant information about its policy rule. The results show that agents exhibit a faster learning speed than the U.S. and a declining perceived inflation persistence. Plus, the model-implied learning mechanism can match the empirical inflation expectations from the Survey on Expectations of Private Sector Specialists. Moreover, there is evidence suggesting that higher degrees of transparency increase the effectiveness of monetary policy in stabilizing the economy.Chapter 2 assesses the role of economic conditions in inflation expectation formation using a Bayesian latent class ordinal model and qualitative survey data from the Michigan Survey of Consumers. The results show evidence that inflation expectations have been formed distinctly depending on the economic conditions faced by individuals. Furthermore, the effect of demographic indicators, such as age, gender, education, and income, on inflation expectations varies with the level of distress of the economy.Lastly, the final chapter develops and estimates a model with informational frictions. Agents are inattentive and form subjective expectations using an economic model. The proposed expectation formation mechanism is estimated using Bayesian methods and tested against rational expectations. The paper yields three novel results. First, the model embedding inattention à la Mankiw and Reis (2002) and subjective expectations under adaptive learning provides the best fit of the data. Secondly, the degree of inattention is susceptible to how the expectation formation process is modeled. In particular, the level of inattention is considerably reduced when I depart from the rational expectation assumption. Finally, this result remains unchanged when tested using real-time macroeconomic series and expectations data from the U.S. Survey of Professional Forecasters.

Departures from full-information rational expectation models give rise to stock price wealth effects which introduce inefficient cyclical fluctuations in the economy. Waves of optimism/pessimism affect beliefs and asset prices which influence aggregate demand through expectation-driven wealth effects. Monetary policy can play an important role in eliminating the non-fundamental effects of belief-driven asset price cycle: reacting symmetrically and transparently to stock prices increases welfare significantly compared to flexible inflation targeting strategies. A quantitative model estimated on US data shows that increasing interest rates by 12 basis points for every 100% rise in stock prices accomplish this goal. Moreover, a nonlinear reaction to stock prices only when capital gains exceed 7% delivers similar efficiency gains.

We propose a model of optimal decision making subject to a memory constraint. The constraint is a limit on the complexity of memory measured using Shannon's mutual information, as in models of rational inattention; but our theory differs from that of Sims (2003) in not assuming costless memory of past cognitive states. We show that the model implies that both forecasts and actions will exhibit idiosyncratic random variation; that average beliefs will also differ from rational-expectations beliefs, with a bias that fluctuates forever with a variance that does not fall to zero even in the long run; and that more recent news will be given disproportionate weight in forecasts. We solve the model under a variety of assumptions about the degree of persistence of the variable to be forecasted and the horizon over which it must be forecasted, and examine how the nature of forecast biases depends on these parameters. The model provides a simple explanation for a number of features of reported expectations in laboratory and field settings, notably the evidence of over-reaction in elicited forecasts documented by Afrouzi et al. (2020) and Bordalo et al. (2020a).

I study the effects of the Covid-19 pandemic on business confidence in 11 Euro area countries and its consequent impact on economic activity. To obtain causal effects, I instrument business confidence with domestic household confidence as well as average household confidence in neighboring countries. I find evidence suggesting that the confidence and expectations channel was an important component to the economic transmission of Covid-19. A one standard deviation drop in business confidence leads to between 5-6 and 9 percent fall in economic activity in the industrial and wholesale and retail trade sectors respectively. These results highlight the importance of managing confidence and expectations in crises episodes.

Confidence dropped universally across countries and sectors during the height of the COVID-19 pandemic in Europe. Latest survey data suggest that confidence is on track for a v-shaped recovery. The swift implementation of stringent containment measures as well as economic stimulus policy measures, along with several other country characteristics, correlate well with both the drop and recovery of confidence across countries.

Assuming that private forecasters learn inflation dynamics to form their inflation expectations and that they believe a hybrid New Keynesian Phillips curve (NKPC) to capture the true data‐generating process of inflation, we aim at establishing the role of backward‐ and forward‐looking information in the inflation expectation formation process. We find that longer term expectations are crucial in shaping shorter horizon expectations. While the influence of backward‐looking information seems to diminish over time, we do not find evidence of a structural break in the expectation formation process of professional forecasters. Our results further suggest that the weight put on longer term expectations does not solely reflect a mean‐reverting process to trend inflation. Rather, it might also capture beliefs about the central bank's long‐run inflation target and its credibility to achieve inflation stabilization.

When the market price of an asset exceeds its fundamental value, rational expectations suggest that agents should expect market prices to fall. This equilibrating relationship is tested using an unbalanced panel of responses from the Federal Reserve Bank of Chicago's quarterly Land Values and Credit Conditions Survey from 1993Q1 - 2018Q2. Empirical results suggest that agricultural bankers expect farmland prices to increase, even when current market prices cannot be justified by underlying fundamentals. Thus, agricultural bankers' short-term farmland price expectations are not consistent with eficient farmland markets. This is the first study of direct, disaggregated farmland price expectations.

What is the role of heterogenous house-price expectations for boom-bust cycles in the housing market? We exploit a unique Dutch panel data set on households' house price expectations and their consumption, savings and housing choices for the period 2003-2016. This period was characterized by a pronounced boom-bust cycle in the housing market. Conditioning the sample on household heads who report non-zero house price expectations, we find that expectations closely track realized house prices. We next develop a structural life-cycle model of the Dutch housing market where we distinguish household types according to their house price expectations. We employ a calibrated model variant to test if observed variations in expectations can account for the housing boom-bust cycle. First results show that our model closely matches the observed fluctuations of the rent-to-price ratio in the data but overshoots the size of the housing boom.

This paper examines the expectations behavior of individual responses in the Survey of Professional Forecasters, the University of Michigan's Survey Research Center survey of consumers, and the ECB Survey of Professional Forecasters. It finds that the most robust feature of all of these expectations measures is that respondents inefficiently revise their forecasts, significantly underreacting to new information. As a consequence, revisions smooth through arriving information, and expectations forget past information at a rapid rate and appear to anchor to the unconditional mean or other salient anchors. The paper then examines the micro-data evidence bearing on the hypotheses tested by Coibion and Gorodnichenko (2015), who suggest that aggregate surveys may conform to key predictions of the sticky-information model of Mankiw and Reis (2002) and/or the noisy-information model of Maækowiak and Wiederholt (2009). This paper finds considerably less coherence with these models in the micro data. The paper also provides evidence that distinguishes this behavior from learning, suggesting that the inefficient incorporation of information is much more important quantitatively than least-squares learning in these expectations measures. Finally, this empirical regularity may bear important implications for macroeconomic dynamics, as illustrated in the last sections of the paper, as it provides a micro-based foundation for an earlier paper's finding that intrinsic persistence in expectations may be a key source of macroeconomic persistence (Fuhrer 2017). The paper sketches a model in which agents' inefficient updating of expectations induces excess smoothness in expectations, imparting persistence to macro variables that is due strictly to the expectations formation process.

In this paper, we make three substantive contributions: first, we use elicited subjective income expectations to identify the levels of permanent and transitory income shocks in a life-cycle framework; second, we use these shocks to assess whether households' consumption is insulated from them; third, we use the shock data to estimate an Euler equation for consumption. We find that households are able to smooth transitory shocks, but adjust their consumption in response to permanent shocks, albeit not fully. The estimates of the Euler equation parameters with and without expectational errors are similar, which is consistent with rational expectations. We break new ground by combining data on subjective expectations about future income from the Michigan Survey with micro data on actual Income from the Consumer Expenditure Survey.

Motivated by the observation that survey expectations of stock returns are inconsistent with rational return expectations under real-world probabilities, we investigate whether alternative expectations hypotheses entertained in the asset pricing literature are consistent with the survey evidence. We empirically test (1) the notion that survey forecasts constitute rational but risk-neutral forecasts of future returns, and (2) the notion that survey fore- casts are ambiguity averse/robust forecasts of future returns. We find that these alternative hypotheses are also strongly rejected by the data, albeit for different reasons. Hypothesis (1) is rejected because survey return forecasts are not in line with risk-free interest rates and because survey expected excess returns are predictable. Hypothesis (2) is rejected because agents are not al- ways pessimistic about future returns, instead often display overly optimistic return expectations. We speculate as to what kind of expectations theories might be consistent with the available survey evidence.

We estimate a New-Keynesian macro model accommodating regime-switching behavior in monetary policy and in macro shocks. Key to our estimation strategy is the use of survey-based expectations for inflation and output. We identify accommodating monetary policy before 1980, with activist monetary policy prevailing most but not 100% of the time thereafter. Systematic monetary policy switched to the activist regime in the 2000-2005 period through an aggressive lowering of interest rates. Discretionary policy spells became less frequent since 1985, but the Volcker period is identified as a discretionary period. Output shocks shift to the low volatility regime around 1985 whereas inflation shocks do so only around 1990, suggesting active monetary policy may have played role in anchoring inflation expectations. Shocks and policy regimes jointly drive the volatility of the macro variables. We provide new estimates of the onset and demise of the Great Moderation and the relative role played by macro-shocks and monetary policy.

New simple forms of deviation from rational expectations (RE) are suggested: temporary near-rational expectations (TNRE) and persistent near-rational expectations (PNRE). The medium-scale DSGE model was estimated with the RE, the TNRE and the PNRE. It was estimated with and without observations from the survey's expectations. The quality of the out-of-sample forecasts was estimated. It is shown that near-rational concepts produce the same advantages as learning, without its disadvantages (including the absence of 'learning expectations' reactions on policy change). The influence of the observed expectations on forecasting quality was analysed.

This paper provides new evidence on the importance of inflation expectations for variation in nominal interest rates, based on both market-based and survey-based measures of inflation expectations. Using the information in TIPS breakeven rates and inflation swap rates, I document that movements in inflation compensation are important for explaining variation in long-term nominal interest rates, both unconditionally as well as conditionally on macroeconomic data surprises. Daily changes in inflation compensation and changes in long-term nominal rates generally display a close statistical relationship. The sensitivity of inflation compensation to macroeconomic data surprises is substantial, and it explains a sizable share of the macro response of nominal rates. The paper also documents that survey expectations of inflation exhibit significant comovement with variation in nominal interest rates, as well as significant responses to macroeconomic news.

In this paper, we consider whether long-term inflation expectations have become better anchored in Brazil, Chile, and Mexico. We do so using survey-based measures as well as financial market-based measures of long-term inflation expectations, where we construct the market-based measures from daily prices on nominal and inflation-linked bonds. This paper is the first to examine the evidence from Brazil and Mexico, making use of the fact that markets for longterm government debt have become better developed over the past decade. We find that inflation expectations have become much better anchored over the past decade in all three countries, as a testament to the improved credibility of the central banks in these countries when it comes to keeping inflation low. That said, one-year inflation compensation in the far future displays some sensitivity to at least one macroeconomic data release per country. However, the impact of these releases is small and it does not appear that investors systematically alter their expectations for inflation as a result of surprises in monetary policy, consumer prices, or real activity variables. Finally, long-run inflation expectations in Brazil appear to have been less well anchored than in Chile and Mexico.

In recent years, survey-based measures of expectations and disagreement have received increasing attention in economic research. Many forecast surveys ask their participants for fixed-event forecasts. Since fixed-event forecasts have seasonal properties, researchers often use an ad-hoc approach in order to approximate fixed-horizon forecasts using fixed-event forecasts. In this work, we derive an optimal approximation by minimizing the mean-squared approximation error. Like the approximation based on the ad-hoc approach, our approximation is constructed as a weighted sum of the fixed-event forecasts, with easily computable weights. The optimal weights tend to differ substantially from those of the ad-hoc approach. In an empirical application, it turns out that the gains from using optimal instead of ad-hoc weights are very pronounced. While our work focusses on the approximation of fixedhorizon forecasts by fixed-event forecasts, the proposed approximation method is very flexible. The forecast to be approximated as well as the information employed by the approximation can be any linear function of the underlying high-frequency variable. In contrast to the ad-hoc approach, the proposed approximation method can make use of more than two such informationcontaining functions.

Although there is much interest in the future retail price of gasoline among consumers, industry analysts, and policymakers, it is widely believed that changes in the price of gasoline are essentially unforecastable given publicly available information. We explore a range of new forecasting approaches for the retail price of gasoline and compare their accuracy with the no-change forecast. Our key finding is that substantial reductions in the mean-squared prediction error (MSPE) of gasoline price forecasts are feasible in real time at horizons up to two years, as are substantial increases in directional accuracy. The most accurate individual model is a VAR(1) model for real retail gasoline and Brent crude oil prices. Even greater reductions in MSPEs are possible by constructing a pooled forecast that assigns equal weight to five of the most successful forecasting models. Pooled forecasts have lower MSPE than the EIA gasoline price forecasts and the gasoline price expectations in the Michigan Survey of Consumers. We also show that as much as 39% of the decline in gas prices between June and December 2014 was predictable.

While there is little question that expectations lie at the heart of much economic decision-making, and therefore at the heart of models of the macroeconomy that hope to reflect such decision-making, how such expectations are formed is an open research question. In earlier work, Fuhrer (2015) showed that empirical estimates of a standard dynamic stochastic general equilibrium (DSGE) model preferred inertia in expectations over price indexation or habit formation as a mechanism to explain the persistence of aggregate time series for output, inflation, and interest rates. A question left open in that paper was why and how expectations might exhibit such inertia. This paper examines the expectations behavior of individual responses in the surveys of the Survey of Professional Forecasters (SPF) and the University of Michigan's Survey Research Center to shed light on that question.

This paper explores the link between agent expectations and housing market dynamics. We focus on shifts in the fundamental driving forces of the economy that are anticipated by rational forward-looking agents, i.e. news shocks. Using Bayesian methods and U.S. data, we find that news-shock-driven-cycles account for a sizable fraction of the variability in house prices and other macroeconomic variables over the business cycle and have also contributed to run-ups in house prices over the last three decades. By exploring the link between news shocks and agent expectations, we show that house price growth was positively related to inflation expectations during the boom of the late 1970’s but negatively related to interest rate expectations during the mid-2000’s housing boom.