Demographic differences in inflation expectations: what do they really mean?

It has often been reported that different demographic groups show persistent differences in their inflation expectations. Some reasonable explanations have been suggested, but most have failed to fully explain these apparent differences. We argue that the demographic differences have been overstated by using the mean to describe differences across demographic groups. When we use the median to describe inflation expectations, we find little meaningful difference across demographic groups.Inflation (Finance) ; Demography

Simple ways to forecast inflation: what works best?

There are many ways to forecast the future rate of inflation, ranging from sophisticated statistical models involving hundreds of variables to hunches based on past experience. We generate a number of forecasts using a simple statistical model and an even simpler estimating rule, adding in various measures thought to be helpful in predicting the course of inflation. Then we compare their forecast accuracy. We find that no single specification outperforms all others over all time periods. For example, the median and 16 percent trimmed-mean measures outperform all other specifications during the 1990s, and survey-based inflation expectations seem to do better during volatile periods.Inflation (Finance) ; Forecasting

Comparison of serum steroidal hormone concentrations in buller steers, riders, and uninterested penmates : implication for the etiology of the buller steer syndrome in North American feedlots

There was a significant relationship between body weight at the time of bulling activity and day 1 rectal temperature (P=0.002). The relationship between body weight at the time of bulling and day 3 rectal temperature was not significant (P=0.31). Analysis of the categorical variables found that the condition of growth hormone implants at the time of bulling did not differ between groups (P = 0.27). Day 1 serum estradiol 17[beta] concentration was significantly different between groups (P=0.05). The 4 steers that had detected-quantified levels of estradiol 17[beta] on day 1 were riders. One buller and 1 control had detected-not quantified levels of estradiol 17[beta] on day 1. The available data support the hypothesis that the rider steer has elevated estradiol 17[beta] at the time of bulling activity as compared to the buller and uninterested pen mates. The results of this study suggest that the rider should be scrutinized as closely as the buller in future studies.The following parameters were recorded and analyzed in rider steers (n=17), buller steers (n=6), and control steers (n=18) at the time of bulling activity: body weight on day 1, rectal temperature on day 1 and 3, implant condition on day 1, and serum hormone concentrations of trenbolone, trenbolone acetate, testosterone, progesterone, and estradiol 17[beta] on day 1 and 3. Day 1 was considered the day of initial bulling activity. The data was analyzed for differences among the variables between the 3 steer groups. Continuous variables included weight at the time of bulling, and rectal temperature on day 1 and 3. Categorical variables included serum hormone concentrations on day 1 and 3, and growth hormone implant condition. Analysis of the continuous variables indicated that body weight at the time of bulling did not differ between groups (P=0.99). Rectal temperature at the time of bulling did not differ between groups (P=0.93), and the rectal temperatures on the third day post bulling activity did not differ between groups (P=0.80)

Ordinal Probit Functional Regression Models with Application to Computer-Use Behavior in Rhesus Monkeys

Research in functional regression has made great strides in expanding to non-Gaussian functional outcomes, however the exploration of ordinal functional outcomes remains limited. Motivated by a study of computer-use behavior in rhesus macaques (\emph{Macaca mulatta}), we introduce the Ordinal Probit Functional Regression Model or OPFRM to perform ordinal function-on-scalar regression. The OPFRM is flexibly formulated to allow for the choice of different basis functions including penalized B-splines, wavelets, and O'Sullivan splines. We demonstrate the operating characteristics of the model in simulation using a variety of underlying covariance patterns showing the model performs reasonably well in estimation under multiple basis functions. We also present and compare two approaches for conducting posterior inference showing that joint credible intervals tend to out perform point-wise credible. Finally, in application, we determine demographic factors associated with the monkeys' computer use over the course of a year and provide a brief analysis of the findings

The usefulness of the median CPI in Bayesian VARs used for macroeconomic forecasting and policy

In this paper, we investigate the forecasting performance of the median Consumer Price Index (CPI) in a variety of Bayesian Vector Autoregressions (BVARs) that are often used for monetary policy. Until now, the use of trimmed-mean price statistics in forecasting inflation has often been relegated to simple univariate or “Phillips-Curve” approaches, thus limiting their usefulness in applications that require consistent forecasts of multiple macro-variables. We find that inclusion of an extreme trimmed-mean measure—the median CPI—improves the forecasts of both core and headline inflation (CPI and personal consumption expenditures price index) across our set of monthly and quarterly BVARs. While the inflation forecasting improvements are perhaps not surprising given the current literature on core inflation statistics, we also find that inclusion of the median CPI improves the forecasting accuracy of the central bank’s primary instrument for monetary policy—the federal funds rate. We conclude with a few illustrative exercises that highlight the usefulness of using the median CPI

The shift to remote work lessens wage-growth pressure

The recent shift to remote work raised the amenity value of employment. As compensation adjusts to share the amenity-value gains with employers, wage-growth pressures moderate. We find empirical support for this mechanism in the wage-setting behavior of U.S. employers, and we develop novel survey data to quantify its force. Our data imply a cumulative wage-growth moderation of 2.0 percentage points over two years. This moderation offsets more than half the real-wage catchup effect that Blanchard (2022) highlights in his analysis of near-term inflation pressures. The amenity-values gains associated with the recent rise of remote work also lower Labor's share of national income by 1.1 percentage points. In addition, the 'unexpected compression' of wages since early 2020 (Autor and Dube, 2022) is partly explained by the same amenity-value effect, which operates differentially across the earnings distribution

Speech Evaluation Assessment: An Analysis of Written Speech Feedback on Instructor Evaluation Forms in the Basic Communication Course

As a critical component of many general education programs, the basic communication course is at the forefront of many assessment efforts. Five years after conducting extensive program assessment using student portfolios, and after implementing revisions to the instructor training program, course directors at Illinois State University conducted another round of portfolio assessment. The present study reveals progress in the specific areas originally targeted for improvement. Additional areas for future revisions to the instructor training program are suggested. Implications for assessment efforts at other institutions are discussed

Bayesian Function-on-Function Regression for Multilevel Functional Data

Medical and public health research increasingly involves the collection of complex and high dimensional data. In particular, functional data—where the unit of observation is a curve or set of curves that are finely sampled over a grid—is frequently obtained. Moreover, researchers often sample multiple curves per person resulting in repeated functional measures. A common question is how to analyze the relationship between two functional variables. We propose a general function-on-function regression model for repeatedly sampled functional data on a fine grid, presenting a simple model as well as a more extensive mixed model framework, and introducing various functional Bayesian inferential procedures that account for multiple testing. We examine these models via simulation and a data analysis with data from a study that used event-related potentials to examine how the brain processes various types of images

Case Report—Myonecrosis in Feedlot Cattle

This report describes an outbreak of disease in a Northwestern Iowa feedlot from January to March of 2001. The cattle had been received in the feedlot in July and August, 2000. Clinical signs included severe lameness, recumbency and death. Lameness was not apparent early in the outbreak and the initial diagnosis was central nervous disease. No infectious or toxic cause could be demonstrated. Due to poor performance, approximately a third of the heifers were held back after the main group was sold. Half of these poor performing heifers displayed visible stiffness. Myonecrosis was demonstrated by significantly elevated serum creatine kinase concentrations in visibly affected cattle as compared to visibly unaffected cattle. Histological lesions were confirmed in cardiac muscle but skeletal muscle was not examined. The cattle had been fed a predominantly corn diet with a liquid supplement containing vitamin E calculated at 12.5 IU/head per day until late in the feeding period, when they were switched to a dry supplement delivering 40 IU/head per day. Serum and liver vitamin E concentrations in sampled animals were below the normal range. Common limitations in field investigations include a failure to test un-affected animals to enable comparisons between groups, testing of animals after disease onset resulting in an inability to demonstrate a temporal relationship between the cause and effect, and small sample sizes. Our case-report suffers to some extent from all these factors; however we suspect that the myonecrosis likely occurred due to Vitamin E deficiency. This presumptive diagnosis is based on the combination of knowledge of vitamin E, creatine kinase, (CK) and Aspartate Amino Transferase (AST) values in the sampled cattle, clinical signs observed, elimination of other possible etiologies and supportive statistical analyses. Investigation of unexplained debilitation in feedlot cattle, especially when accompanied by lameness, should include evaluations of serum and/or liver vitamin E concentrations, serum (AST) and (CK) concentration, muscle histology, and ration vitamin E concentration

Thirty Meter Telescope astrometry error budget

The Thirty Meter Telescope (TMT) with its first-light multi-conjugate adaptive optics system, NFIRAOS, and high-resolution imager, IRIS, is expected to take differential astrometric measurements with an accuracy on the order of tens of micro arcsec. This requires the control, correction, characterization and calibration of a large number of error sources and uncertainties, many of which have magnitudes much in excess of this level of accuracy. In addition to designing the observatory such that very high precision and accuracy astrometric observations are enabled, satisfying the TMT requirements can only be achieved by a careful calibration, observation and data reduction strategy. In this paper, we present descriptions of the individual errors sources, how and when they apply to different astrometry science cases and the mitigation methods required for each of them, as well as example results for individual error terms and the overall error budgets for a variety of different science cases