Evaluating the Survey of Professional Forecasters probability distributions of expected inflation based on derived event probability forecasts

Techniques are proposed for evaluating forecast probabilities of events. The tools are especially useful when, as in the case of the Survey of Professional Forecasters (SPF) expected probability distributions of inflation, recourse cannot be made to the method of construction in the evaluation of the forecasts. The tests of efficiency and conditional efficiency are applied to the forecast probabilities of events of interest derived from the SPF distributions, and supplement a whole-density evaluation of the SPF distributions based on the probability integral transform approach.

Taylor principle and inflation stability in emerging market countriesw

The goal of this paper is to evaluate the validity of the Taylor principle for inflation control in 12 developing countries that use inflation targeting regimes: Brazil, Chile, Colombia, Hungary, Israel, Mexico, Peru, Philippines, Poland, South Africa, Thailand and Turkey. The test is based on a state-space model to determine when each country has followed the principle; then a threshold unit root test is used to verify if the stationarity of the deviation of the expected inflation from its target depends on compliance with the Taylor principle. The results show that such compliance leads to the stationarity of the deviation of the expected inflation from its target in all cases. Furthermore, in most cases, non-compliance with the Taylor principle leads to nonstationary deviation of the expected inflation.

Time-dependent or state-dependent pricing? Evidence from firms’ response to inflation shocks

This paper proposes a test for distinguishing between time-dependent and state-dependent pricing based on whether the timing of pricing changes is affected by realized or expeted inflation. Using Brazilian data and exploring a large discrepancy between realized and expected inflation in 2002-3, we obtain a strong relation between expected inflation and duration of price spells, but little effect of inflation shocks on the frequency of price adjustment. The results thus support models with timedependent pricing, where the timing for following changes is optimally chosen whenever firms adjust prices

Nonlinear mixture autoregressive model: economic applications

The aim of this dissertation is to model economic variables by a mixture autoregressive (MAR) model. The MAR model is a generalization of linear autoregressive (AR) model. The MAR -model consists of K linear autoregressive components. At any given point of time one of these autoregressive components is randomly selected to generate a new observation for the time series. The mixture probability can be constant over time or a direct function of a some observable variable. Many economic time series contain properties which cannot be described by linear and stationary time series models. A nonlinear autoregressive model such as MAR model can a plausible alternative in the case of these time series. In this dissertation the MAR model is used to model stock market bubbles and a relationship between inflation and the interest rate. In the case of the inflation rate we arrived at the MAR model where inflation process is less mean reverting in the case of high inflation than in the case of normal inflation. The interest rate move one-for-one with expected inflation. We use the data from the Livingston survey as a proxy for inflation expectations. We have found that survey inflation expectations are not perfectly rational. According to our results information stickiness play an important role in the expectation formation. We also found that survey participants have a tendency to underestimate inflation. A MAR model has also used to model stock market bubbles and crashes. This model has two regimes: the bubble regime and the error correction regime. In the error correction regime price depends on a fundamental factor, the price-dividend ratio, and in the bubble regime, price is independent of fundamentals. In this model a stock market crash is usually caused by a regime switch from a bubble regime to an error-correction regime. According to our empirical results bubbles are related to a low inflation. Our model also imply that bubbles have influences investment return distribution in both short and long run.

Hotel Valuation Software, Version 4.0

[Updated August 2016] The Hotel Valuation Software, freely available from Cornell’s Center for Hospitality Research, has been updated to reflect the many changes in the 11th Edition of the Uniform System of Accounts for the Lodging Industry (USALI). Version 4.0 of the Hotel Valuation Software provides numerous enhancements over the original tool from 2011. In addition to a significant increase in functionality and an update to reflect the 11th edition of the USALI, Version 4.0 takes advantage of the power of the latest release of Microsoft Excel®. Note that Version 4.0 works only on a PC running Microsoft Windows, it does not work on a Mac running OS X. Users desiring an OS X compatible version should click here (Labeled as Version 2.5). 酒店评估软件手册和三个程序（点击这里 ) Users desiring a Mandarin version of the Hotel Valuation Software should click here The Hotel Valuation Software remains the only non-proprietary computer software designed specifically to assist in the preparation of market studies, forecasts of income and expense, and valuations for lodging property. The software provides an accurate, consistent, and cost-effective way for hospitality professionals to forecast occupancy, revenues and expenses and to perform hotel valuations. Version 4.0 of the Hotel Valuation Software includes the following upgrades – a complete update to reflect the 11th edition of the USALI – the most significant change to the chart of accounts in a generation, an average daily rate forecasting tool, a much more sophisticated valuation module, and an optional valuation tool useful in periods of limited capital liquidity. Using established methodology, the Hotel Valuation Software is a sophisticated tool for lodging professionals. The tool consists of three separate software programs written as Microsoft Excel files and a software users' guide. The tool is provided through the generosity of HVS and the School of Hotel Administration. The three software modules are: Room Night Analysis and Average Daily Rate: Enables the analyst to evaluate the various competitive factors such as occupancy, average room rate, and market segmentation for competitive hotels in a local market. Calculates the area-wide occupancy and average room rate, as well as the competitive market mix. Produce a forecast of occupancy and average daily rate for existing and proposed hotels in a local market. The program incorporates such factors as competitive occupancies, market segmentation, unaccommodated demand, latent demand, growth of demand, and the relative competitiveness of each property in the local market. The program outputs include ten-year projections of occupancy and average daily rate. Fixed and Variable Revenue and Expense Analysis: The key to any market study and valuation is a supportable forecast of revenues and expenses. Hotel revenue and expenses are comprised of many different components that display certain fixed and variable relationships to each other. This program enables the analyst to input comparable financial operating data and forecast a complete 11-year income and expense statement by defining a small set of inputs: The expected future occupancy levels for the subject hotel Base year operating data for the subject hotel Fixed and variable relationships for revenues and expenses Expected inflation rates for revenues and expenses Hotel Capitalization Software: A discounted cash flow valuation model utilizing the mortgage-equity technique forms the basis for this program. Values are produced using three distinct underwriting criteria: A loan-to-value ratio, in which the size of the mortgage is based on property value. A debt coverage ratio (also known as a debt-service coverage ratio), in which the size of the mortgage is based on property level cash flow, mortgage interest rate, and mortgage amortization. A debt yield, in which the size of the mortgage is based on property level cash flow. By entering the terms of typical lodging financing, along with a forecast of revenue and expense, the program determines the value that provides the stated returns to the mortgage and equity components. The program allows for a variable holding period from four to ten years The program includes an optional model useful during periods of capital market illiquidity that assumes a property refinancing during the holding period

Speculative attacks, openness and crises

In this paper we propose a dynamic stochastic general equilibrium model to evaluate financial adjustments that some emerging market economies went through to overcome external crises during the latest decades, such as default and local currency devaluation. We assume that real devaluation can be used to avoid external debt default, to improve trade balance and to reduce the real public debt level denominated in local currency. Such effects increase the government ability to deal with external crisis, but also have costs in terms of welfare, related to expected inflation, reductions in private investments and higher interest to be paid over the public debt. We conclude that openness improves expected welfare as it allows for a better devaluation-response technology against crises. We also present results for 32 middle-income countries, verifying that the proposed model can indicate, in a stylized way, the preferences for default-devaluation options and the magnitude of the currency depreciation required to overcome 48 external crises occurred as from 1971. Finally, as we construct our model based on the Cole-Kehoe self-fulfilling debt crisis model ([7]), adding local debt and trade, it is important to say that their policy alternatives to leave the crisis zone remains in our extended model, namely, to reduce the external debt level and to lengthen its maturity.

Stochastic growth and monetary policy: the impacts on the term structure of interest rates

This paper builds a simple, empirically-verifiable rational expectations model for term structure of nominal interest rates analysis. It solves an stochastic growth model with investment costs and sticky inflation, susceptible to the intervention of the monetary authority following a policy rule. The model predicts several patterns of the term structure which are in accordance to observed empirical facts: (i) pro-cyclical pattern of the level of nominal interest rates; (ii) countercyclical pattern of the term spread; (iii) pro-cyclical pattern of the curvature of the yield curve; (iv) lower predictability of the slope of the middle of the term structure; and (v) negative correlation of changes in real rates and expected inflation at short horizons.

Um novo teste empírico para modelos teóricos de precificação

Este artigo propõe um novo teste para distinção entre modelos macroeconômicos de precificação. Onde testes antigos concluíram haver uma relação negativa entre inflação corrente e duração de um preço, indicando estado-dependência, nosso teste indica que a relação verdadeira é entre inflação esperada e duração do preço, indicando tempo-dependência-endógena. Argumentamos que os resultados previamente encontrados possivelmente sofreram de viés de variável omitida.

Os determinantes macroeconômicos da estrutura a termo das expectativas de inflação no Brasil

Este trabalho visa analisar a dinâmica das expectativas de inflação em função das condições macroeconômicas. Para tal, extraímos as curvas de inflação implícita na curva de títulos públicos pré-fixados e estimamos um modelo de fatores dinâmicos para sua estrutura a termo. Os fatores do modelo correspondem ao nível, inclinação e curvatura da estrutura a termo, que variam ao longo do tempo conforme os movimentos no câmbio, na inflação, no índice de commodities e no risco Brasil implícito no CDS. Após um choque de um desvio padrão no câmbio ou na inflação, a curva de inflação implícita se desloca positivamente, especialmente no curto prazo e no longo prazo. Um choque no índice de commodities também desloca a curva de inflação implícita positivamente, afetando especialmente a parte curta da curva. Em contraste, um choque no risco Brasil desloca a curva de inflação implícita paralelamente para baixo.

Determinantes da taxa de aluguel nas cidades de São Paulo e Rio de Janeiro

Este trabalho analisa a variação da taxa de aluguel e do custo de moradia nas cidades de São Paulo e Rio de Janeiro para o período de Janeiro de 2008 a Janeiro de 2014 utilizando uma abordagem quantitativa com base na expectativa de longo prazo da taxa de juros reais, na expectativa de inflação e na valorização do preço dos imóveis em uma janela de 1 ano. Os resultados indicam que a expectativa de longo prazo da taxa de juros reais tem um impacto relevante na variação da taxa de aluguel durante o período abordado, bem como a expectativa de inflação, mas em magnitude menor, enquanto a valorização passada de 1 ano não tem poder explicativo sobre a taxa de aluguel.

Choques de oferta e política monetária na economia brasileira: Uma análise do impacto dos preços das commodities na inflação entre 2002 e 2014

Há mais de uma década o controle dos níveis de preço na economia brasileira é realizado dentro do escopo do Regime de Metas de Inflação, que utiliza modelos macroeconômicos como instrumentos para guiar as tomadas de decisões sobre política monetária. Após um período de relativo êxito (2006 - 2009), nos últimos anos apesar dos esforços das autoridades monetárias na aplicação das políticas de contenção da inflação, seguindo os mandamentos do regime de metas, esta tem se mostrado resistente, provocando um debate em torno de fatores que podem estar ocasionando tal comportamento. Na literatura internacional, alguns trabalhos têm creditado aos choques de oferta, especialmente aos desencadeados pela variação dos preços das commodities, uma participação significativa na inflação, principalmente em economias onde os produtos primários figuram como maioria na pauta exportadora. Na literatura nacional, já existem alguns trabalhos que apontam nesta mesma direção. Sendo assim, buscou-se, como objetivo principal para o presente estudo, avaliar como os choques de oferta, mais especificamente os choques originados pelos preços das commodities, têm impactado na inflação brasileira e como e com que eficiência a política monetária do país tem reagido. Para tanto, foi estimado um modelo semiestrutural contendo uma curva de Phillips, uma curva IS e duas versões da Função de Reação do Banco Central, de modo a verificar como as decisões de política monetária são tomadas. O método de estimação empregado foi o de Autorregressão Vetorial com Correção de Erro (VEC) na sua versão estrutural, que permite uma avaliação dinâmica das relações de interdependência entre as variáveis do modelo proposto. Por meio da estimação da curva de Phillips foi possível observar que os choques de oferta, tanto das commodities como da produtividade do trabalho e do câmbio, não impactam a inflação imediatamente, porém sua relevância é crescente ao longo do tempo chegando a prevalecer sobre o efeito autorregressivo (indexação) verificado. Estes choques também se apresentaram importantes para o comportamento da expectativa de inflação, produzindo assim, uma indicação de que seus impactos tendem a se espalhar pelos demais setores da economia. Através dos resultados da curva IS constatou-se a forte inter-relação entre o hiato do produto e a taxa de juros, o que indica que a política monetária, por meio da fixação de tal taxa, influencia fortemente a demanda agregada. Já por meio da estimação da primeira função de reação, foi possível perceber que há uma relação contemporânea relevante entre o desvio da expectativa de inflação em relação à meta e a taxa Selic, ao passo que a relação contemporânea do hiato do produto sobre a taxa Selic se mostrou pequena. Por fim, os resultados obtidos com a segunda função de reação, confirmaram que as autoridades monetárias reagem mais fortemente aos sinais inflacionários da economia do que às movimentações que acontecem na atividade econômica e mostraram que uma elevação nos preços das commodities, em si, não provoca diretamente um aumento na taxa básica de juros da economia.

Essays in Macro Finance

I study the link between capital markets and sources of macroeconomic risk. In chapter 1 I show that expected inflation risk is priced in the cross section of stock returns even after controlling for cash flow growth and volatility risks. Motivated by this evidence I study a long run risk model with a built-in inflation non-neutrality channel that allows me to decompose the real stochastic discount factor into news about current and expected cash flow growth, news about expected inflation and news about volatility. The model can successfully price a broad menu of assets and provides a setting for analyzing cross sectional variation in expected inflation risk premium. For industries like retail and durable goods inflation risk can account for nearly a third of the overall risk premium while the energy industry and a broad commodity index act like inflation hedges. Nominal bonds are exposed to expected inflation risk and have inflation premiums that increase with bond maturity. The price of expected inflation risk was very high during the 70's and 80's, but has come down a lot since being very close to zero over the past decade. On average, the expected inflation price of risk is negative, consistent with the view that periods of high inflation represent a "bad" state of the world and are associated with low economic growth and poor stock market performance. In chapter 2 I look at the way capital markets react to predetermined macroeconomic announcements. I document significantly higher excess returns on the US stock market on macro release dates as compared to days when no macroeconomic news hit the market. Almost the entire equity premium since 1997 is being realized on days when macroeconomic news are released. At high frequency, there is a pattern of returns increasing in the hours prior to the pre-determined announcement time, peaking around the time of the announcement and dropping thereafter.

Genomic inflation factors under polygenic inheritance

Population structure, including population stratification and cryptic relatedness, can cause spurious associations in genome-wide association studies (GWAS). Usually, the scaled median or mean test statistic for association calculated from multiple single-nucleotide-polymorphisms across the genome is used to assess such effects, and 'genomic control' can be applied subsequently to adjust test statistics at individual loci by a genomic inflation factor. Published GWAS have clearly shown that there are many loci underlying genetic variation for a wide range of complex diseases and traits, implying that a substantial proportion of the genome should show inflation of the test statistic. Here, we show by theory, simulation and analysis of data that in the absence of population structure and other technical artefacts, but in the presence of polygenic inheritance, substantial genomic inflation is expected. Its magnitude depends on sample size, heritability, linkage disequilibrium structure and the number of causal variants. Our predictions are consistent with empirical observations on height in independent samples of ~4000 and ~133,000 individuals.