02158cam a22002537 4500001000700000003000500007005001700012008004100029100002100070245013900091260006600230490004200296500001900338520095700357530006101314538007201375538003601447690011501483690011201598710004201710830007701752856003801829856003701867w16634NBER20180423210256.0180423s2010 mau||||fs|||| 000 0 eng d1 aBurnside, Craig.10aIdentification and Inference in Linear Stochastic Discount Factor Models with Excess Returnsh[electronic resource] /cCraig Burnside. aCambridge, Mass.bNational Bureau of Economic Researchc2010.1 aNBER working paper seriesvno. w16634 aDecember 2010.3 aWhen excess returns are used to estimate linear stochastic discount factor (SDF) models, researchers often adopt a normalization of the SDF that sets its mean to 1, or one that sets its intercept to 1. These normalizations are often treated as equivalent, but they are subtly different both in population, and in finite samples. Standard asymptotic inference relies on rank conditions that differ across the two normalizations, and which can fail to differing degrees. I first establish that failure of the rank conditions is a genuine concern for many well known SDF models in the literature. I also describe how failure of the rank conditions can affect inference, both in population and in finite samples. I propose using tests of the rank conditions not only as a diagnostic device, but also for model reduction. I show that this model reduction procedure has desirable size and power properties in a Monte Carlo experiment with a calibrated model. aHardcopy version available to institutional subscribers. aSystem requirements: Adobe [Acrobat] Reader required for PDF files. aMode of access: World Wide Web. 7aC3 - Multiple or Simultaneous Equation Models • Multiple Variables2Journal of Economic Literature class. 7aG12 - Asset Pricing • Trading Volume • Bond Interest Rates2Journal of Economic Literature class.2 aNational Bureau of Economic Research. 0aWorking Paper Series (National Bureau of Economic Research)vno. w16634.4 uhttp://www.nber.org/papers/w1663441uhttp://dx.doi.org/10.3386/w16634