Conditioning as disintegration

Conditional probability distributions seem to have a bad reputation when it comes to rigorous treatment of conditioning. Technical arguments are published as manipulations of Radon–Nikodym derivatives, although we all secretly perform heuristic calculations using elementary definitions of conditional probabilities. In print, measurability and averaging properties substitute for intuitive ideas about random variables behaving like constants given particular conditioning information.
One way to engage in rigorous, guilt-free manipulation of conditional distributions is to treat them as disintegrating measures—families of probability measures concentrating on the level sets of a conditioning statistic. In this paper we present a little theory and a range of examples—from EM algorithms and the Neyman factorization, through Bayes theory and marginalization paradoxes—to suggest that disintegrations have both intuitive appeal and the rigor needed for many problems in mathematical statistics.     

Perceptions of facilitators of a keypad‐based group support system

Organizations are using Group Support Systems (GSSs) to improve the quality of group meetings. Keypad‐based GSSs are a widely used form of this technology, yet there has been little research on their use and effects. This paper reports the findings of a survey of facilitators of a particular keypad GSS. Facilitators indicate that keypad technology improves the quality of meetings for a variety of tasks in a range of group settings and cultures. The findings are in general agreement with field studies of workstation‐based systems.     

Monetary–fiscal policy interactions and fiscal stimulus

Increases in government spending trigger substitution effects—both inter- and intra-temporal—and a wealth effect. The ultimate impacts on the economy hinge on current and expected monetary and fiscal policy behavior. Studies that impose active monetary policy and passive fiscal policy typically find that government consumption crowds out private consumption: higher future taxes create a strong negative wealth effect, while the active monetary response increases the real interest rate. This paper estimates Markov-switching policy rules for the United States and finds that monetary and fiscal policies fluctuate between active and passive behavior. When the estimated joint policy process is imposed on a conventional new Keynesian model, government spending generates positive consumption multipliers in some policy regimes and in simulated data in which all policy regimes are realized. The paper reports the model's predictions of the macroeconomic impacts of the American Recovery and Reinvestment Act's implied path for government spending under alternative monetary–fiscal policy combinations.     

Inflation and the fiscal limit

We use a rational expectations framework to assess the implications of rising debt in an environment with a “fiscal limit”. The fiscal limit is defined as the point where the government no longer has the ability to finance higher debt levels by increasing taxes, so either an adjustment to fiscal spending or monetary policy must occur to stabilize debt. We give households a joint probability distribution over the various policy adjustments that may occur, as well as over the timing of when the fiscal limit is hit. One policy option that stabilizes debt is a passive monetary policy, which generates a burst of inflation that devalues the existing nominal debt stock. The probability of this outcome places upward pressure on inflation expectations and poses a substantial challenge to a central bank pursuing an inflation target. The distribution of outcomes for the path of future inflation has a fat right tail, revealing that only a small set of outcomes imply dire inflationary scenarios. Avoiding these scenarios, however, requires the fiscal authority to renege on some share of future promised transfers.     

Impact of the 2014 Suspension Agreement on sugar between the United States and Mexico

In December 2014, the U.S. and Mexico agreed to a suspension agreement that set a $22.25/cwt import price floor on U.S. sugar imports from Mexico. A partial equilibrium trade model was developed to estimate the economic impact the agreement would have had if it had been in effect from 2008 to 2014. In years when the price floor would have been binding, on average, U.S. producers would have gained $138 million and Mexican producers would have lost $218 million. However, total Mexican welfare would have actually increased by $11.5 million. Furthermore, the average price floor that would have maximized total Mexican welfare over that period is $22.76/cwt. Also, under certain supply and demand elasticity conditions, the average price floor that would have maximized joint U.S. and Mexican producer welfare over that period is $21.91/cwt. The latter two estimates are both close to the actual price floor agreed to in the 2014 Suspension Agreement.     

Alternative Approaches to Compensation and Producer Rights

When policies are changed, it is not uncommon for losers to be compensated. Economic theory and quantitative analysis are useful in determining the efficiency gains/losses associated with a policy change, but are little help in deciding what the approach to compensation should be. The amount of compensation varies, depending on, in part, the political clout of the parties being negatively affected by a policy change—compensation is what politicians and the sector demanding compensation can agree on. We formulate four approaches to producer compensation within the context of the Ontario Tobacco Transition Program, where producers would have suffered losses in the absence of compensation. The approaches range from providing zero compensation to providing compensation based on the entire value of the tobacco quota. The Canadian government chose the latter and compensated producers for the termination of the tobacco quota program based on an approach that far exceeded other possible compensation approaches.     

Real-time forecasts of economic activity for Latin American economies

Macroeconomic policy decisions in real-time are based on the assessment of current and future economic conditions. Crucially, these assessments are made difficult by the presence of incomplete and noisy data. The problem is more acute for emerging market economies, where most economic data are released infrequently with a (sometimes substantial) lag. This paper evaluates nowcasts and forecasts of real GDP growth using five models for ten Latin American countries. The results indicate the flow of monthly data helps to improve forecast accuracy, and the dynamic factor model consistently produces more accurate nowcasts and forecasts relative to other model specifications, across most of the countries we consider.