Download e-book for kindle: Aggregate Money Demand Functions: Empirical Applications in by Dennis L. Hoffman

By Dennis L. Hoffman

ISBN-10: 9400918143

ISBN-13: 9789400918146

ISBN-10: 9401073082

ISBN-13: 9789401073080

The econometric outcomes of nonstationary facts have extensive ranging im­ plications for empirical learn in economics. particularly, those matters have implications for the learn of empirical kin similar to a cash call for func­ tion that hyperlinks macroeconomic aggregates: genuine funds balances, genuine source of revenue and a nominal rate of interest. conventional financial idea predicts that those nonsta­ tionary sequence shape a cointegrating relation and hence, that the dynamics of a vector technique created from those variables generates detailed styles. Re­ cent econometric advancements designed to deal with nonstationarities have replaced the process empirical examine within the quarter, yet many basic demanding situations, for instance the difficulty of identity, stay. This e-book represents the efforts undertaken by way of the authors lately with a purpose to be certain the results that nonstationarity has for the research of combination cash call for kinfolk. we've introduced jointly an empirical technique that we discover valuable in undertaking empirical examine. the various paintings was once undertaken throughout the authors' sabbatical sessions and we want to recognize the beneficiant help of Arizona country collage and Michigan kingdom college respectively. Professor Hoffman needs to recognize the help of the Fulbright-Hays beginning that supported sabbattical examine in Europe and separate help of the Council of a hundred summer time learn software at Arizona kingdom University.

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Extra resources for Aggregate Money Demand Functions: Empirical Applications in Cointegrated Systems

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Perhaps the best strategy is to compare results obtained from several of these approaches and examine whether the preponderance of evidence makes a convincing case for stationarity, nonstationarity, or cointegration. At the same time it may prove very difficult to prove definitively whether stochastic or broken deterministic trends provide the best explanation for the behavior of a given series. 6 In this light it may be prudent to examine 6Perhaps the best example of this difficulty is a series such as the inflation rate{ln(p/p-l)) where it is unclear whether the underlying process(ln(p)) is 1(1) with breaks in trend that correspond with major oil shock episodes or actually an 1(2) process.

The origin of this aggregate relation lies in the work of Baumol (1952), Tobin (1956) and Friedman (1956) while Lucas (1988) demonstrates how micro foundation for the relationship may be established in a representative agent setting. , Johansen and Juselius (1990), Hoffman and Rasche (1991), King, Plosser, Stock and Watson (1991)) suggests that a cointegrating or long-run relation does indeed prevail among the variables that comprise a money demand model. 10). Despite this theoretical foundation, the evidence in favor of a stable longrun money demand relationship is not completely one-sided.

The values of TO and T1 are C*(L)ct and -C(1)JLO - C*(L)JLl' respectively, where C(L) = C(1) + C*(L). Clearly Tl depends upon the assumptions that prevail about /30; "10, /31 and "II' Johansen separates the various trend specifications into five categories. Ho(r) maintains the most general specification where /30, "10, /31 and "II are all nonzero. In this case the cointegrating vector: /3, removes stochastic and quadratic trend. 2. EVIDENCE OF COINTEGRATION 39 However, a linear trend of (3' T1 t typically remains in (3' Zt since there is no reason for (3 to be orthogonal to C*(L).

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Aggregate Money Demand Functions: Empirical Applications in Cointegrated Systems by Dennis L. Hoffman


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