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During the 2001 International Symposium on Forecasting in Atlanta, Peg Young approached me to inquire whether I would be interested in developing an output measure of the transportation sector for the purpose of macroeconomic forecasting. At that time, the Bureau of Transportation Statistics (BTS) of the U.S. Department of Transportation (US DOT) was interested in developing such a project in order for it to join the company of other federal agencies that produce monthly U.S economic indicators. During next two years with a research grant from US DOT at the University of Albany, SUNY, entitled “The Theoretical Development, Selection, and Testing of Economic Indicators for the Transportation Industry,” I developed the transportation services index (TSI) with the assistance of Herman Stekler as the consultant and graduate student Wenxiong Yao as the research assistant of the project. Needless to say, we had to make numerous visits to Washington to consult with DOT staff and for presentations. Identifying monthly indicators for different sectors of the transportation sector was difficult because transportation indicators had virtually disappeared from business cycle research since the early 1950s. The research project was completed in a year and during the summer of 2003. I went to US DOT headquarters in Washington DC with Wenxiong Yao to train its staff to produce the index on a monthly basis. On January 2, 2004, after ringing the opening bell of the New York Stock Exchange, the U.S. Transportation Secretary Norman Mineta announced the roll out of the TSI as a new economic indicator intended to measure the total freight and passenger activity in the U.S. economy. Six weeks later, the first monthly release of the TSI on March 10, 2004, marked the official beginning of the series that has been released and updated every month since then, and all reports are now available at http://www.bts.gov/xml/tsi/src/index.xml. The new indicator did not escape the media attention. On April 5, 2004, issue of Business Week, columnist James Mehring noted, “The index provides another sorely needed measure of the service sector. Services constitute about two-thirds of the economy, yet few government reports cover the…[It] should become a new crystal ball for economists and investors to peer into.” On March 15, 2010, the front page of Wall Street Journal reported the recent upward movement in the freight component of TSI, suggesting that the latest recession might have turned around.

From the standpoint of a policy maker who has access to a number of expert forecasts, the uncertainty of a combined or ensemble forecast should be interpreted as that of a typical forecaster randomly drawn from the pool. This uncertainty formula should incorporate forecaster discord, as justified by (i) disagreement as a component of combined forecast uncertainty, (ii) the model averaging literature, and (iii) central banks’ communication of uncertainty via fan charts. Using new statistics to test for the homogeneity of idiosyncratic errors under the joint limits with both T and n approaching infinity simultaneously, the authors find that some previously used measures can significantly underestimate the conceptually correct benchmark forecast uncertainty.

In this volume, we have studied the cyclical behavior of numerous business cycle indicators from the U.S. transportation sector and studied how they are related to those of the overall economy. Our study began with the conceptualization of what constitutes the transportation services sector, identifying relevant monthly indicators from the private sector and the government, and finally putting them together to construct a monthly measure of output of the transportation services sector. The challenge was to develop an indicator that will be available promptly soon after a month with other widely reported monthly indicators such as the index of industrial production, Institute for Supply Management (ISM) surveys, CPI, index of leading indicators, etc. and is not subject to much data revisions. Since monthly activity measures of major transportation services sectors such as trucking and railroads are produced by private membership organizations, use of these data in the production of official statistics in the public sector needed skillful persuasion of government officials. Bureau of Transportation Statistics (BTS) releases the preliminary number for the latest month and replaces the number for the oldest preliminary month with a revised number. All other revisions are held until an annual comprehensive revision of the transportation services output (TSI). It is gratifying to see that the arrangement of cooperation between the transportation department and these private service organizations are working out seamlessly, and TSI continues to get the media attention.

With the increasing importance of the service-providing sectors, information from these sectors has become essential to the understanding of contemporary business cycles. Contribution of services to GDP during postwar recessions is clearly recorded in Table 4.1. On average, decline in real GDP during recessions would have been at least 70% more severe without the stabilization effect from services. Moore (1987) noted that the ability of the service sectors to create jobs has differentiated business cycles since the 1980s, and has led economy-wide recessions to be shorter and less severe. This is reflected as mild declines in employment of service sectors and its dominance in the total nonfarm employment, as plotted in Figure 4.1a. The growth in real GDP by major type of products obtained from National NIPA is depicted in Figure 4.1b. Since 1985, services never had a negative growth, which has muted the volatility in goods and structures, and resulted in more stable economy measured by total GDP (see also McConnell and Perez-Quiros, 2000).

Since the transportation sector plays an important role in the initiation and propagation of business cycles, in previous chapters we developed output [transportation services output (TSI)] and other indicators to construct an index of coincident indicators for the U.S. transportation sector to identify its current state. We defined the reference cycle, including both business and growth cycles for this sector beginning in 1979 using both the conventional National Bureau of Economic Research (NBER) method and modern time series models. A one-to-one correspondence between cycles in the transportation sector and those in the aggregate economy was found; however, both business and growth cycles of transportation often start earlier and end later than those of the overall economy. Although the knowledge and inference based on coincident indicators can serve as an important reference for planning and other decision-making processes, these indicators are also subject to substantial lag due to data collection, processing and revision, underscoring the need to develop a system of leading indicators for the industry. Thus, in this chapter, we construct an index of leading indicators for the transportation sector as a forecasting tool using rigorous statistical procedures.

The authors examine whether or not applicants and recipients of federal disability insurance (DI) inflate their self-assessed health (SAH) problems relative to others. To do this, the authors employ a technique which uses anchoring vignettes. This approach allows them to examine how various cohorts of the population interpret survey questions associated with subjective self-assessments of health. The results of the analysis suggest that DI participants do inflate the severity of a given health problem, but by a small but significant degree. This tendency to exaggerate the severity of disability problems is much more apparent among those with more education (especially those with a college degree). In contrast, racial minorities tend to underestimate severity ratings for a given disability vignette when compared to their white peers.

Transportation plays a central role in facilitating economic activities across sectors and between regions and thus should be essential to business cycle research. In this chapter, we identify four coincident indicators representing different aspects of the transportation sector. Foremost among them is the index of transportation services output (TSI) presented in the previous chapter. Following the long-standing methodology of National Bureau of Economic Research (NBER) business cycle research, the other three indicators that we include are payroll, personal consumption and employment – all pertaining to the transportation sector. Using a composite of the four indicators, we define the classical business cycle and growth cycle chronologies for the transportation sector. We find that, relative to the economy, business cycles in the transportation sector have an average lead of nearly 6 months at peaks and an average lag of 2 months at troughs. Similar to transportation business cycles, growth slowdowns in this sector also last longer than the economy-wide slowdowns by a few months. This study underscores the importance of transportation indicators in monitoring cyclical movements in the aggregate economy.

In this chapter we develop a monthly output index of the U.S. transportation sector covering air, rail, water, truck, transit, and pipeline activities. We call it the transportation services index (TSI). Separate indexes for freight and passenger are also constructed. Before the development of TSI, there was no comprehensive monthly measure of the economic activity by all modes of transportation. Since policymakers are increasingly concerned about the critical role transportation plays in enabling economic growth, monitoring of TSI can provide them with insights about the current and future state of the economy. Fortunately we find that our monthly transportation services output index (TSI), which is based on a new measurement approach, matches very well with the annual transportation output figures produced by the Bureau of Labor Statistics (BLS) and the Bureau of Economic Analysis (BEA). Some analysis reported in this chapter indicate that the cyclical movements in the transportation output appear to be more synchronized with the growth slowdowns rather than full-fledged recessions of the U.S. economy. The index has led the turning points of the 6 National Bureau of Economic Research (NBER)-defined growth cycles over the period with an average lead-time of 6 months at peaks and 5 months at troughs.