Digital Commons Network^™

In Pursuit Of Consumption-Based Forecasting, Charles Chase, Kenneth B. Kahn

Marketing Faculty Publications

[Introduction] Today's most mature, most sophisticated, best-in-class forecasting is what we call consumption-based forecasting (CBF). In contrast, the least sophisticated companies typically do not forecast at all, but rather set financial targets based on management expectations. Companies beginning to use statistical forecasting techniques usually take a supply-centric orientation, relying on time series techniques applied to shipment and/or order history. The next stage of progression is to incorporate promotions data, economic data, and market data alongside supply-centric data so that regression and other advanced analytics can be used. Companies pursing CBF utilize even more advanced capabilities to capture, examine, and understand …

An Investigation Into The Likelihood That A Centrally Planned Economy Can Provide Greater Economic Good Than Spontaneous Order Created By The Free Market, Douglas W. Cardell

Doctoral Dissertations and Projects

This paper will address whether it is possible for an economy, planned by experts, to result in greater economic good than can be achieved by spontaneous order created by the combination of individual choices that make up the free market? This paper approaches the question by studying the viability of economic forecasting because planning an economy requires making economic forecasts. There are at least three domains that impact forecasting: the nature of forecasting and modeling in general in a chaotic environment, the effect of asset bubbles, and the impact of black swan events. There is a great deal of research …

Forecasting Economic Activity Using The Yield Curve: Quasi-Real-Time Applications For New Zealand, Australia And The Us, Todd Henry, Peter C.B. Phillips

Cowles Foundation Discussion Papers

Inversion of the yield curve has come to be viewed as a leading recession indicator. Unsurprisingly, some recent instances of inversion have attracted attention from economic commentators and policymakers about possible impending recessions. Using a variety of time series models and recent innovations in econometric method, this paper conducts quasi-real-time forecasting exercises to investigate whether the predictive capability of the yield curve extends to forecasting economic activity in general and whether removing the term premium component from yields affects forecast accuracy. The empirical findings for the US, Australia, and New Zealand show that forecast performance is not improved either by …

Forecasting Skills In Experimental Markets: Illusion Or Reality?, Brice Corgnet, Cary Deck, Mark Desantis, David Porter

ESI Working Papers

Using experimental asset markets, we study the situation of a financial analyst who is trying to infer the fundamental value of an asset by observing the market’s history. We find that such capacity requires both standard cognitive skills (IQ) as well as social and emotional skills. However, forecasters with high emotional skills tend to perform worse when market mispricing is high as they tend to give too much emphasis to the noisy signals from market data. By contrast, forecasters with high social skills perform especially well in markets with high levels of mispricing in which their skills could help them …

Forecasting With Unbalanced Panel Data, Badi Baltagi, Long Liu

Center for Policy Research

This paper derives the best linear unbiased prediction (BLUP) for an unbalanced panel data model. Starting with a simple error component regression model with unbalanced panel data and random effects, it generalizes the BLUP derived by Taub (1979) to unbalanced panels. Next it derives the BLUP for an unequally spaced panel data model with serial correlation of the AR(1) type in the remainder disturbances considered by Baltagi and Wu (1999). This in turn extends the BLUP for a panel data model with AR(1) type remainder disturbances derived by Baltagi and Li (1992) from the balanced to the unequally spaced panel …

Short- And Medium-Term Car Registration Forecasting Based On Selected Macro And Socio-Economic Indicators In European Countries, Lubor Homolka, Vu Minh Ngo, Drahomíra Pavelková, Bach Tuan Le, Bruce Dehning

Accounting Faculty Articles and Research

The automotive industry plays a key role in the European economy. In this paper, we determine which macro and socio-economic indicators have significant predictive power on car registrations - a proxy to automotive sector performance - across European countries. Contrary to the current literature which mainly focuses on long-term forecasting, we built our models on the highly seasonal monthly data of a medium-term period to make short-term forecasts. Our approach utilises predictors identified by the literature review. Presented models are built on the Vector Autoregressive models and are accompanied by formal tests, such as the Granger causality test. We have …

Is A Driverless Future Also Jobless?, Erica L. Groshen, John Paul Macduffie, Susan Helper, Charles Carson

Upjohn Institute Policy and Research Briefs

No abstract provided.

Fiscal Surprises At The Fomc, Dean D. Croushore, Simon Van Norden

Economics Faculty Publications

We examine a new set of U.S. fiscal forecasts from FOMC briefing books. The forecasts were precisely those presented to monetary policymakers and include frequently updated estimates covering six complete business cycles and several fiscal-policy regimes. We detail the performance of forecast federal expenditures, revenues, surpluses, and structural surpluses in terms of accuracy, bias, and efficiency. We find that forecast errors can be economically large, even at relatively short forecast horizons. While economic activity became less volatile after 1990, fiscal policy became harder to forecast. Finally, cyclically adjusted deficit forecasts appear to be overoptimistic around both business cycle peaks and …

Preparing U.S. Workers And Employers For An Autonomous Vehicle Future, Erica L. Groshen, Susan Helper, John Paul Macduffie, Charles Carson

Upjohn Institute Technical Reports

No abstract provided.

Forecasting Labor Force Participation At The Regional Level In The United States: The Case Of Maine, Maryam Kashkooli

Honors College

This project attempts to investigate the future of labor force participation in Maine using an econometric forecasting approach. Forecasting has become an increasingly popular form of statistical analysis which uses historical distributions to help estimate future distributions of econometric models. There exists extensive literature on forecasting employment, however the literature on forecasting labor force participation is relatively small. I adapt existing econometric models and make use of time series information on sociodemographic factors such as age and net migration in order to determine how Maine’s changing demographic structure is affecting its labor force and how these effects will carry on …

Ecio Model Operators Guide, Randall Jackson, Péter Járosi

Regional Research Institute Resource Documents

The National Energy Technology Laboratory (NETL)/ West Virginia University (WVU) Econometric Input-Output (ECIO) model is a time-series enabled hybrid econometric input-output (IO) model that combines the capabilities of econometric modeling with the strengths of IO modeling. The model was developed and designed specifically for estimating the income and employment impacts of the development and deployment of new energy technologies over a given forecast period. The ECIO model consists of a macroeconomic econometric model of the United States (U.S.) national economy and an inter-industry model that reflects the interdependence of all the industries in the economy. These two components have three …

Range-Based Volatility, Expected Stock Returns, And The Low Volatility Anomaly, Benjamin M. Blau, Ryan J. Whitby

Economics and Finance Faculty Publications

One of the foundations of financial economics is the idea that rational investors will discount stocks with more risk (volatility), which will result in a positive relation between risk and future returns. However, the empirical evidence is mixed when determining how volatility is related to future returns. In this paper, we examine this relation using a range-based measure of volatility, which is shown to be theoretically, numerically, and empirically superior to other measures of volatility. In a variety of tests, we find that range-based volatility is negatively associated with expected stock returns. These results are robust to time-series multifactor models …

Macroconstants Of Development: A New Benchmark For The Strategic Development Of Advanced Countries And Firms, Andrey V. Bystrov, Vyacheslav N. Yusim, Tamilla Curtis

Publications

This research proposed a new indicator of countries’ development called “macroconstants of development”. The literature review indicates that the concept of "macroconstants of development" is not used at the moment in neither the theory nor the practice of industrial policy. Research of longitudinal data of total GDP, GDP per capita and their derivatives for most countries of the world was conducted. An analysis of statistical information has been done by employing econometric analyses.

Based on the analysis of the statistical data, which characterizes the development of large, technologically advanced countries in ordinary conditions, it was identified that the average acceleration …

Macroeconomic Variables Effect On Us Market Volatility Using Mc-Garch Model, Jang Hyung Cho, Ahmed Elshahat

Faculty Publications

Forecasting equity volatility was thoroughly investigated during the past three decades. The majority based their forecasts on the dynamics of the underlying equity time series. They helped better understand the dynamics of these time series and understand different aspects of volatility. Other models went a step further to include the effect of news announcement on equity volatility. The vast majority ignored the effect of macroeconomic variable or the state of the economy. This paper proposes a volatility-forecasting model that accounts for effect of fundamental macroeconomic variables that reflect the state of the economy. The explanatory variables used measure the stage …

The Mythology Of Game Theory, Mathew D. Mccubbins, Mark Turner, Nick Weller

Faculty Scholarship

Non-cooperative game theory is at its heart a theory of cognition, specifically a theory of how decisions are made. Game theory's leverage is that we can design different payoffs, settings, player arrays, action possibilities, and information structures, and that these differences lead to different strategies, outcomes, and equilibria. It is well-known that, in experimental settings, people do not adopt the predicted strategies, outcomes, and equilibria. The standard response to this mismatch of prediction and observation is to add various psychological axioms to the game-theoretic framework. Regardless of the differing specific proposals and results, game theory uniformly makes certain cognitive assumptions …

The Pragmatist’S Guide To Comparative Effectiveness Research, Amitabh Chandra, Anupam B. Jena, Jonathan Skinner

Dartmouth Scholarship

No abstract provided.

Analyzing And Forecasting Business Cycles In A Small Open Economy: A Dynamic Factor Model For Singapore, Hwee Kwan Chow, Keen Meng Choy

Research Collection School Of Economics

A dynamic factor model is applied to a large panel dataset of Singapore’s macroeconomic variables and global economic indicators with the initial objective of analysing business cycles in a small open economy. The empirical results suggest that four common factors – which can broadly be interpreted as world, regional, electronics and domestic economic cycles – capture a large proportion of the co-variation in the quarterly time series. The estimated factor model also explains well the observed fluctuations in real economic activity and price inflation, leading us to use it in forecasting Singapore’s business cycles. We find that the forecasts generated …

Analyzing And Forecasting Business Cycles In A Small Open Economy: A Dynamic Factor Model For Singapore, Hwee Kwan Chow, Keen Meng Choy

Research Collection School Of Economics

A dynamic factor model is applied to a large panel dataset of Singapore’s macroeconomic variables and global economic indicators with the initial objective of analyzing business cycles in a small open economy. The empirical results suggest that four common factors are present in the quarterly time series, which can broadly be interpreted as world, regional, electronics and domestic economic cycles. The estimated factor model explains well the observed fluctuations in real economic activity and price inflation, leading us to use it in forecasting Singapore’s business cycles. We find that the forecasts generated by the factors are generally more accurate than …

Pricing Options By Simulation Using Realized Volatility, David E. Allen, Michael Mcaleer, Marcel Scharth

Research outputs pre 2011

A growing literature advocates the use of high-frequency data for the purpose of volatility estimation. However, despite the successes in modeling the conditional mean of realized volatility empirical evaluations of this class of models outside the realm of short run forecasting is limited. How can realized volatility be used for pricing options? What are the modeling qualities introduced by realized volatility models for pricing derivatives? In this short paper, we propose an options pricing framework based on a new realized volatility model that captures all the relevant empirical regularities of the realized volatility series of the S&P 500 index. We …

Is American Health Care Uniquely Inefficient?, Alan M. Garber, Jonathan Skinner

Dartmouth Scholarship

No abstract provided.

Will The Stork Return To Europe And Japan? Understanding Fertility Within Developed Nations, James Feyrer, Bruce Sacerdote, Ariel Dora Stern

Dartmouth Scholarship

We seek to explain the differences in fertility rates across high-income countries by focusing on the interaction between the increasing status of women in the workforce and their status in the household, particularly with regards to child care and home production. We observe three distinct phases in women's status generated by the gradual increase in women's workforce opportunities. In the earliest phase, characteristic of the 1950s and 1960s in the United States, women earn low wages relative to men and are expected to shoulder all of the child care at home. As a result, most women specialize in home production …

A Dynamic-Trend Exponential Smoothing Model, Don Miller, Dan Williams

Publications and Research

Forecasters often encounter situations in which the local pattern of a time series is not expected to persist over the forecasting horizon. Since exponential smoothing models emphasize recent behavior, their forecasts may not be appropriate over longer horizons. In this paper, we develop a new model in which the local trend line projected by exponential smoothing converges asymptotically to an assumed future long-run trend line, which might be an extension of a historical long-run trend line. The rapidity of convergence is governed by a parameter. A familiar example is an economic series exhibiting persistent long-run trend with cyclic variation. This …

Financial Variables As Predictors Of Real Output Growth, Anthony S. Tay

Research Collection School Of Economics

We investigate two methods for using daily stock returns to forecast, and update forecasts of, quarterly real output growth. Both methods aggregate daily returns in some manner to form a single stock market variable. We consider (i) augmenting the quarterly AR(1) model for real output growth with daily returns using a nonparametric Mixed Data Sampling (MIDAS) setting, and (ii) augmenting the quarterly AR(1) model with the most recent r -day returns as an additional predictor. We discover that adding low frequency stock returns (up to annual returns, depending on forecast horizon) to a quarterly AR(1) model improves forecasts of output …

Mixing Frequencies: Stock Returns As A Predictor Of Real Output Growth, Anthony S. Tay

Research Collection School Of Economics

We investigate two methods for using daily stock returns to forecast, and update forecasts of, quarterly real output growth. Both methods aggregate daily returns in some manner to form a single stock market variable. We consider (i) augmenting the quarterly AR(1) model for real output growth with daily returns using a nonparametric Mixed Data Sampling (MIDAS) setting, and (ii) augmenting the quarterly AR(1) model with the most recent r -day returns as an additional predictor. We find that our mixed frequency models perform well in forecasting real output growth.

Forecasting The Global Electronics Cycle With Leading Indicators: A Bayesian Var Approach, Hwee Kwan Chow, Keen Meng Choy

Research Collection School Of Economics

Developments in the global electronics industry are typically monitored by tracking indicators that span a whole spectrum of activities in the sector. However, these indicators invariably give mixed signals at each point in time, thereby hampering attempts at prediction. In this paper, we propose a unified framework for forecasting the global electronics cycle by constructing a VAR model that captures the economic interactions between putative leading indicators representing expectations, orders, inventories and prices. The ability of the indicators to presage world semiconductor sales is first examined by Granger causality tests. Subsequently, an impulse response analysis confirms the leading qualities of …

Commodity Price Fluctuations: A Century Of Analysis, Walter C. Labys

Regional Research Institute Working Papers

Commodity prices again! The twentieth century has only been the latest spectator to the impacts and importance of commodity price fluctuations. It is reasonably well known that commodity price records have come down to us from the ancient civilizations of India, Mesopotamia, Egypt, Greece and Rome. Earlier in the century, formal research began on the relationships between agricultural demand, supply and prices in a market context. This research not only evolved in sophistication but extended to mineral and energy commodities. Also at the beginning of the century, some of the earliest work took place on applying statistical methods to price …

Seasonality, Nonstationarity And The Structural Forecasting Of The Index Of Industrial Production, Eugene Kouassi, Walter C. Labys, François B. Aka

Regional Research Institute Working Papers

In this paper we focus on two ‘STS’ models suitable for forecasting the index of industrial production. The first model requires that the index be transformed with a first and seasonal difference filters. The second model considers the index in its second difference filter, while seasonality is modeled with a constant and seasonal dummy variables. Tests designed to discriminate empirically between these two models are also conducted. Our results prefer the performance of the second model, particularly when the conventional ML estimation procedure is replaced by the ALS procedure. This process together with appropriate seasonal adjustment advances the possibility of …

Forecasting New Zealand's Real Gdp, Aaron F. Schiff, Peter C.B. Phillips

Cowles Foundation Discussion Papers

Recent time series methods are applied to the problem of forecasting New Zealand’s real GDP. Model selection is conducted within autoregressive (AR) and vector autoregressive (VAR) classes, allowing for evolution in the form of the models over time. The selections are performed using the Schwarz (1978) BIC and the Phillips-Ploberger (1996) PIC criteria. The forecasts generated by the data-determined AR models and an international VAR model are found to be competitive with forecasts from fixed format models and forecasts produced by the NZIER. Two illustrations of the methodology in conditional forecasting settings are performed with the VAR models. The first …

Low Inflation: The Surprise Of The 1990s, Dean D. Croushore

Economics Faculty Publications

For most of the 1990s, forecasters have been predicting an upturn in inflation. Yet, over that same period, the United States has experienced stable or declining inflation. Why have forecasts been at odds with reality? And why does it matter? In this article, Dean Croushore considers some answers to these questions and explains why inflation is the economic surprise of the decade.

Econometric Modeling As Information Aggregation, Ray C. Fair, Robert J. Shiller

Cowles Foundation Discussion Papers

The information contained in the forecasts from two econometric models can be compared by regressing the actual change in the variable forecasted on the two forecasts of the change. We do such comparisons in this paper, where the forecasts are based only on information through the period prior to the first period of the forecast. If a model’s forecast is statistically significant in such a regression, we conclude that the model captures information not in the other model whose forecast is also included in the regression. The models studied include the Fair model, vector autoregressive (VAR) models estimated by ordinary …