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There are other income factors, besides the aggregate national income and labour income factors discussed in Ch. 4, that contribute as much uncertainty to the incomes of individuals and organizations as do many risks currently traded in financial markets. If those who retail insurance policies against risks of changes in values of claims on incomes or service flows are to be able to tailor their insurance to the various exposures that their different clients have to these risks, they will want to layoff in hedging markets the risks of changes in these income factors that influence them because they are providing the insurance policies. This chapter considers some of the most salient of these other markets: real estate, unincorporated business, and privately held corporations, consumer and producer price index futures, agriculture, and art and collectibles. It also presents some ideas on systematic approaches to finding other markets, including modelling the tendency for co‐movement of incomes and inferring the underlying factors, i.e. looking for the major risk factors to incomes for which new markets would be most useful.

Presents improved estimates of the cost of living and the real wages of labourers in the western part of the Netherlands. The results show that even in this relatively dynamic economy there was a decline in real wages during the Early Modern Period.

The most widely used total or headline inflation measure is the Consumer Price Index (CPI). Inflation is often said to be “persistent increases in the general level of prices, or a persistent decline in the purchasing power of money, caused by an increase in available currency and credit beyond available quantities of goods and services.” Inflation measures developed based on this approach represent partial measures only, because they pertain to a number of individual transactions in specific markets. The cost of this subset of goods and services is then compared in two distinct periods to yield a measure of inflation.

This chapter examines welfare measures when they are made without cardinal utility functions to understand the properties of the aggregate dollar changes in utility computed in a conventional Harberger (1971) analysis. The Hatta (1977) decomposition is used to show how, for individual consumers, dollars are a reliable proxy for utility, whenever policy changes are incrementally small. This decomposition finds that income effects are a scaling coefficient on the efficiency effects from marginal policy changes that play no role in single consumer economies. A number of different approaches are examined to account for distributional effects when there are heterogenous consumers.

Debt of households has been rising rapidly since 1995. The debt to income ratio of the bottom 95 percent of the income distribution has risen well above 140 percent. The same measure for the top five percent has been stable near 60 percent for 25 years. Low interest rates, easy credit terms, subprime mortgages, and mortgage refinancings have all stimulated consumer borrowing. The housing bubble, nationwide, encouraged consumers to extract cash from their properties. Panel regressions relating per capita household debt to declining income shares by state of the bottom 80 percent show that as income shares decline household debt rises. Economic insecurity objectively measured has been rising. The share of household budgets spent on the necessities of housing, health care and education have risen for all quintiles. Prices of those three have exceeded inflation for 20 years. Stagnant incomes and rising prices for those necessities have lured households to take on more debt to sustain their standard of living.

This chapter provides a detailed history of the evolution of the Consumer Price Index (CPI), and a comprehensive review of the various commissions formed to study it. It reveals the long-standing nature of many CPI issues that are still controversial today. Apart from providing various CPI reviews, the authors present their views on the alternative methodological foundations for a consumer price index and, in particular, debate the merits of the economic or Cost-of-Living Index (COLI) approach versus the Cost-of-Goods Index (COGI). It is found that the COLI approach to CPI index construction is superior to either the COGI or test approaches, but it is also noted that the test approach can be useful on occasion as a supplement to the economic approach to index construction.

The measurement of the output of the medical care system is necessary to assess the productivity levels and growth of a country's economy and medical care system. Medical price indexes have uses other than those involving output and productivity measurement. In the United States, both within the health sector and more generally, contracts occasionally contain provisions that depend on growth of the medical Consumer Price Index (CPI). The CPI and the Producer Price Index (PPI) are also employed in updating fee schedules for certain administered pricing schemes and payments to some health plans. This chapter reviews the measurement issues underlying the construction of medical care price indexes. It describes procedures employed by the U.S. Bureau of Labor Statistics in the construction of its medical CPIs and PPIs (including recent revisions and changes). It also discusses alternative notions of medical care output that involve the price of a treatment episode rather than the prices of fixed bundles of inputs. Finally, the chapter outlines salient features of a new price index for health expenditures.

Robert Shiller created the most commonly cited time series for nonfarm home values and prices between 1920 and 1940 by splicing a series developed by Grebler, Blank, and Winnick (1956) for 1890 to 1934 with a new series based on 30 asking prices per year in five major cities to extend the series from 1934 to 1953. We develop and examine several alternative measures of housing prices over the period 1920 to 1940. All series show that nominal housing prices fell by 20-30 percent from a peak in the late 1920s to a trough around 1933 and 1934. However, there is substantial disagreement about the values circa 1920 and 1940. For 1920 the Shiller Hybrid suggests that housing values were 5-7 percent higher than in 1930. In contrast, all alternative series show that housing values in 1920 were 6-20 percent lower than in 1930. For 1940 the Shiller Hybrid index rises within 5 percent of the 1930 value. In contrast, all of the other series have 1940 values that are 18.7 to 35.6 percent lower than in 1930. In summary, the alternative measures suggest much stronger growth in nonfarm house prices between 1920 and 1930 and much less recovery by 1940 than the Shiller Hybrid series.

This chapter provides a description of basic price index techniques, the intuition underlying their construction, and how one interprets the results. In particular, the chapter provides instructions on how to construct fixed-based and chained indexes and discusses some of the common problems, like substitution bias, the new goods problem and chain drift. It also discusses the intuition behind two popular interpretations of price indexes: the cost of living index interpretation and the constant-quality price index interpretation. The formulas considered are: Laspeyres, Paasche, Fisher Ideal, Tornquist, Jevons.

This chapter describes the Barclays mortgage-based securities (MBS) index pricing and returns methodologies and highlights the price and return dynamics that result. The Barclays Fixed-Rate MBS Index maps individual agency MBS pools to “annual aggregates,” or “generics,” according to program, coupon, and vintage. The index contains only these annual aggregates (about 320 as of June 2015) and has rules for calculating index prices and returns that may differ from what investors may use for their MBS holdings. In particular, the index calculates index prices assuming same-day settlement, whereas many portfolio managers rely on PSA (Pay As You Earn Settlement Agreement) prices that assume settlement at the next PSA settlement date which may be a month away or longer. The motivation behind the use of same-day settlement prices to calculate returns is to avoid jumps in month-to-date (MTD) returns unrelated to market movements.