Using common features to understand the behavior of metal-commodity prices and forecast them at different horizons

The objective of this article is to study (understand and forecast) spot metal price levels and changes at monthly, quarterly, and annual horizons. The data to be used consists of metal-commodity prices in a monthly frequency from 1957 to 2012 from the International Financial Statistics of the IMF on individual metal series. We will also employ the (relatively large) list of co-variates used in Welch and Goyal (2008) and in Hong and Yogo (2009) , which are available for download. Regarding short- and long-run comovement, we will apply the techniques and the tests proposed in the common-feature literature to build parsimonious VARs, which possibly entail quasi-structural relationships between different commodity prices and/or between a given commodity price and its potential demand determinants. These parsimonious VARs will be later used as forecasting models to be combined to yield metal-commodity prices optimal forecasts. Regarding out-of-sample forecasts, we will use a variety of models (linear and non-linear, single equation and multivariate) and a variety of co-variates to forecast the returns and prices of metal commodities. With the forecasts of a large number of models (N large) and a large number of time periods (T large), we will apply the techniques put forth by the common-feature literature on forecast combinations. The main contribution of this paper is to understand the short-run dynamics of metal prices. We show theoretically that there must be a positive correlation between metal-price variation and industrial-production variation if metal supply is held fixed in the short run when demand is optimally chosen taking into account optimal production for the industrial sector. This is simply a consequence of the derived-demand model for cost-minimizing firms. Our empirical evidence fully supports this theoretical result, with overwhelming evidence that cycles in metal prices are synchronized with those in industrial production. This evidence is stronger regarding the global economy but holds as well for the U.S. economy to a lesser degree. Regarding forecasting, we show that models incorporating (short-run) commoncycle restrictions perform better than unrestricted models, with an important role for industrial production as a predictor for metal-price variation. Still, in most cases, forecast combination techniques outperform individual models.

Using common features to understand the behavior of metal-commodity prices and forecast them at different horizons

The objective of this article is to study (understand and forecast) spot metal price levels and changes at monthly, quarterly, and annual frequencies. Data consists of metal-commodity prices at a monthly and quarterly frequencies from 1957 to 2012, extracted from the IFS, and annual data, provided from 1900-2010 by the U.S. Geological Survey (USGS). We also employ the (relatively large) list of co-variates used in Welch and Goyal (2008) and in Hong and Yogo (2009). We investigate short- and long-run comovement by applying the techniques and the tests proposed in the common-feature literature. One of the main contributions of this paper is to understand the short-run dynamics of metal prices. We show theoretically that there must be a positive correlation between metal-price variation and industrial-production variation if metal supply is held fixed in the short run when demand is optimally chosen taking into account optimal production for the industrial sector. This is simply a consequence of the derived-demand model for cost-minimizing firms. Our empirical evidence fully supports this theoretical result, with overwhelming evidence that cycles in metal prices are synchronized with those in industrial production. This evidence is stronger regarding the global economy but holds as well for the U.S. economy to a lesser degree. Regarding out-of-sample forecasts, our main contribution is to show the benefits of forecast-combination techniques, which outperform individual-model forecasts - including the random-walk model. We use a variety of models (linear and non-linear, single equation and multivariate) and a variety of co-variates and functional forms to forecast the returns and prices of metal commodities. Using a large number of models (N large) and a large number of time periods (T large), we apply the techniques put forth by the common-feature literature on forecast combinations. Empirically, we show that models incorporating (short-run) common-cycle restrictions perform better than unrestricted models, with an important role for industrial production as a predictor for metal-price variation.

Learning in peer-to-peer markets: evidence from Airbnb

Peer-to-peer markets are highly uncertain environments due to the constant presence of shocks. As a consequence, sellers have to constantly adjust to these shocks. Dynamic Pricing is hard, especially for non-professional sellers. We study it in an accommodation rental marketplace, Airbnb. With scraped data from its website, we: 1) describe pricing patterns consistent with learning; 2) estimate a demand model and use it to simulate a dynamic pricing model. We simulate it under three scenarios: a) with learning; b) without learning; c) with full information. We have found that information is an important feature concerning rental markets. Furthermore, we have found that learning is important for hosts to improve their profits.

On the consistency of arbitrary money-demand functions with the Sidrauski and the shopping-time models

This paper investigates which properties money-demand functions have to satisfy to be consistent with multidimensional extensions of Lucasí(2000) versions of the Sidrauski (1967) and the shopping-time models. We also investigate how such classes of models relate to each other regarding the rationalization of money demands. We conclude that money demand functions rationalizable by the shoppingtime model are always rationalizable by the Sidrauski model, but that the converse is not true. The log-log money demand with an interest-rate elasticity greater than or equal to one and the semi-log money demand are counterexamples.

Forecasting electricity demand using generalized long memory

This paper studies the electricity hourly load demand in the area covered by a utility situated in the southeast of Brazil. We propose a stochastic model which employs generalized long memory (by means of Gegenbauer processes) to model the seasonal behavior of the load. The model is proposed for sectional data, that is, each hour’s load is studied separately as a single series. This approach avoids modeling the intricate intra-day pattern (load profile) displayed by the load, which varies throughout days of the week and seasons. The forecasting performance of the model is compared with a SARIMA benchmark using the years of 1999 and 2000 as the out-of-sample. The model clearly outperforms the benchmark. We conclude for general long memory in the series.

Forecasting electricity load demand: analysis of the 2001 rationing period in Brazil

This paper studies the electricity load demand behavior during the 2001 rationing period, which was implemented because of the Brazilian energetic crisis. The hourly data refers to a utility situated in the southeast of the country. We use the model proposed by Soares and Souza (2003), making use of generalized long memory to model the seasonal behavior of the load. The rationing period is shown to have imposed a structural break in the series, decreasing the load at about 20%. Even so, the forecast accuracy is decreased only marginally, and the forecasts rapidly readapt to the new situation. The forecast errors from this model also permit verifying the public response to pieces of information released regarding the crisis.

Three essays on local demand for public services

Local provision of public services has the positive effect of increasing the efficiency because each locality has its idiosyncrasies that determine a particular demand for public services. This dissertation addresses different aspects of the local demand for public goods and services and their relationship with political incentives. The text is divided in three essays. The first essay aims to test the existence of yardstick competition in education spending using panel data from Brazilian municipalities. The essay estimates two-regime spatial Durbin models with time and spatial fixed effects using maximum likelihood, where the regimes represent different electoral and educational accountability institutional settings. First, it is investigated whether the lame duck incumbents tend to engage in less strategic interaction as a result of the impossibility of reelection, which lowers the incentives for them to signal their type (good or bad) to the voters by mimicking their neighbors’ expenditures. Additionally, it is evaluated whether the lack of electorate support faced by the minority governments causes the incumbents to mimic the neighbors’ spending to a greater extent to increase their odds of reelection. Next, the essay estimates the effects of the institutional change introduced by the disclosure on April 2007 of the Basic Education Development Index (known as IDEB) and its goals on the strategic interaction at the municipality level. This institutional change potentially increased the incentives for incumbents to follow the national best practices in an attempt to signal their type to voters, thus reducing the importance of local information spillover. The same model is also tested using school inputs that are believed to improve students’ performance in place of education spending. The results show evidence for yardstick competition in education spending. Spatial auto-correlation is lower among the lame ducks and higher among the incumbents with minority support (a smaller vote margin). In addition, the institutional change introduced by the IDEB reduced the spatial interaction in education spending and input-setting, thus diminishing the importance of local information spillover. The second essay investigates the role played by the geographic distance between the poor and non-poor in the local demand for income redistribution. In particular, the study provides an empirical test of the geographically limited altruism model proposed in Pauly (1973), incorporating the possibility of participation costs associated with the provision of transfers (Van de Wale, 1998). First, the discussion is motivated by allowing for an “iceberg cost” of participation in the programs for the poor individuals in Pauly’s original model. Next, using data from the 2000 Brazilian Census and a panel of municipalities based on the National Household Sample Survey (PNAD) from 2001 to 2007, all the distance-related explanatory variables indicate that an increased proximity between poor and non-poor is associated with better targeting of the programs (demand for redistribution). For instance, a 1-hour increase in the time spent commuting by the poor reduces the targeting by 3.158 percentage points. This result is similar to that of Ashworth, Heyndels and Smolders (2002) but is definitely not due to the program leakages. To empirically disentangle participation costs and spatially restricted altruism effects, an additional test is conducted using unique panel data based on the 2004 and 2006 PNAD, which assess the number of benefits and the average benefit value received by beneficiaries. The estimates suggest that both cost and altruism play important roles in targeting determination in Brazil, and thus, in the determination of the demand for redistribution. Lastly, the results indicate that ‘size matters’; i.e., the budget for redistribution has a positive impact on targeting. The third essay aims to empirically test the validity of the median voter model for the Brazilian case. Information on municipalities are obtained from the Population Census and the Brazilian Supreme Electoral Court for the year 2000. First, the median voter demand for local public services is estimated. The bundles of services offered by reelection candidates are identified as the expenditures realized during incumbents’ first term in office. The assumption of perfect information of candidates concerning the median demand is relaxed and a weaker hypothesis, of rational expectation, is imposed. Thus, incumbents make mistakes about the median demand that are referred to as misperception errors. Thus, at a given point in time, incumbents can provide a bundle (given by the amount of expenditures per capita) that differs from median voter’s demand for public services by a multiplicative error term, which is included in the residuals of the demand equation. Next, it is estimated the impact of the module of this misperception error on the electoral performance of incumbents using a selection models. The result suggests that the median voter model is valid for the case of Brazilian municipalities.

Low expectations, low demand : when should the government intervene?

Este trabalho estuda o impacto de diferentes políticas que procuram mitigar falhas de coordenação em um ambiente macroeconômico. Abordamos questões relativas ao timing dos estímulos econômicos. Quando o governo deveria começar a incentivar a economia? Deveria gastar mais para prevenir crises ou para tirar a economia da recessão quando os fundamentos estão melhorando? Como o estímulo deve alterar a complementaridade estratégica? Para responder a estas perguntas, construímos um modelo macroeconômico dinâmico com concorrência monopolística e decisões de investimento sequenciais. Aplicando resultados da literatura teórica de jogos dinâmicos com fricções, selecionamos um único equilíbrio neste modelo, nos dando um instrumental tratável para a análise de políticas. Nossos resultados sugerem que o governo não deveria viesar incentivos nem para a prevenção de crises nem para resgatar a economia quando esta já está em crise.

Predicting Amazon Deforestation through the deterninants of demand for agricultural land

This paper develops a model of deforestation pressure in the Amazon. It is based on the determinants of demand for agricultural land, i.e. the interactions between population dynamics, urbanization and the growth of local markets, land prices, and government spending and policies. The mo deI is estimated using data from the period 1970 - 1985, and predictions for the period 1985 - 2010 are made under explicit assumptions about the underlying factors of deforestation. The predictions indicate that economic growth in the Amazon is likely to continue at high rates even if the federal government abandons its aggressive development policy. Deforestation will be much smaller if they do, though, since the active development policies tend to promote wasteful use of land.

Demand- side resistance to creative destruction in schumpeterian growth theory

The Schumpelerian model of endogeno~s growlh is generalized with lhe introduction of stochastic resislance. by agenls other Ihan producers. to lhe innovations which drive growth. This causes a queue to be formcd of innovations, alrcady discovered, bUI waiting to be adopled~ A slationary stochastic equilibrium (SSE) is obtained when the queue is stable~ It is shown that in the SSE, such resistance will always reduce lhe average growth iate hut it may increa~e wclfare in certain silualions. In an example, Ihis is when innovatiuns are small anti monopoly power great. The cont1icl hetween this welfare motive for resistance and those of rent-seeking innovalors.may well explain why growth rates differ.

Demand-pull stagflation

This paper explores the possibility of stagflation emanating exc1usively from monetaJy sbocks, without concurrent supply shocks or shifts in potential output. This arises in connection with a tight money paradox. in the context of a fiscal theory of the price leveI. The paper exhibits perfect foresight equilibria with output and inflation fluctuating in opposite direetions as a consequence of small monetary shocks, and also following changes in monetaJy policy regime that launch the economy into hyperinflation or that produce dramatic stabilization of already high inflation. For that purpose, an analytically convenient dynamic general equilibrium macro model is deve10ped wbere nominal rigidities are represented by a cross between staggered two-period contracts and state dependent price adjustment in the presence of menu costs.

Monetary dynamics in a general equilibrium version of the Baumol-Tobin model

I study the welfare cost of inflation and the effect on prices after a permanent increase in the interest rate. In the steady state, the real money demand is homogeneous of degree one in income and its interest-rate elasticity is approximately equal to −1/2. Consumers are indifferent between an economy with 10% p.a. inflation and one with zero inflation if their income is 1% higher in the first economy. A permanent increase in the interest rate makes the price level to drop initially and inflation to adjust slowly to its steady state level.

Phase transition of demand explained by the heterogeneity of consumers' intrinsic preferences

In 1991 Gary S. Becker presented A Note on Restaurant Pricing and Other Examples of Social In uences on Price explaining why many successful restaurants, plays, sporting events, and other activities do not raise their prices even with persistent excess demand. The main reason for this is due to the discontinuity of stable demands, which is explained in Becker's (1991) analysis. In the present paper we construct a discrete time stochastic model of socially interacting consumers deciding for one of two establishments. With this model we show that the discontinuity of stable demands, proposed by Gary S. Becker, depends crucially on an additional factor: the dispersion of the consumers' intrinsic preferences for the establishments.

Nonlinear pricing beyond the demand profile approach

Wilson [16] introduced a general methodology to deal with monopolistic pricing in situations where customers have private information on their tastes (‘types’). It is based on the demand profile of customers: For each nonlinear tariff by the monopolist the demand at a given level of product (or quality) is the measure of customers’ types whose marginal utility is at least the marginal tariff (‘price’). When the customers’ marginal utility has a natural ordering (i.e., the Spence and Mirrlees Condition), such demand profile is very easy to perform. In this paper we will present a particular model with one-dimensional type where the Spence and Mirrlees condition (SMC) fails and the demand profile approach results in a suboptimal solution for the monopolist. Moreover, we will suggest a generalization of the demand profile procedure that improves the monopolist’s profit when the SMC does not hold.

Demand expectations and the timing of stimulus policies

This paper proposes a simple macroeconomic model with staggered investment decisions. The model captures the dynamic coordination problem arising from demand externalities and fixed costs of investment. In times of low economic activity, a firm faces low demand and hence has less incentives for investing, which reinforces firms’ expectations of low demand. In the unique equilibrium of the model, demand expectations are pinned down by fundamentals and history. Owing to the beliefs that arise in equilibrium, there is no special reason for stimulus at times of low economic activity.