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barrier is removed. The unexpected behavior is when the gray ball continues to jump when the barrier is not there. Now we have to change our ideas about the goal of the gray ball. Perhaps it likes jumping Other people are much more interesting than small gray balls. We watch their movements all the time and try to predict what they are going to do next. Walking along the street, we must predict which way the person coming toward us is going to dodge. We get this prediction right so often that when we both dodge the same way this is a special event marked by embarrassed smiles. We pay particular attention to other people s eyes. When watching someone s eyes, we can detect very small movements. We can detect an eye movement of less than 2 millimeters when standing up to 1 meter away from the face. This sensitivity to eye movements allows us to take the rst step into someone else s mental world. From the position of a person s eyes we can tell very accurately where they are looking. And if we know where people are looking, then we can discover what they are interested in. When we look at Figure 6.3, we know that Larry is interested in the ball and we can t help looking at it as well. I see the Professor of English on the other side of the crowded room. The rst thing I notice is that she is not looking at me. So who is she

notional principal amount Any speci ed amount of money or property that, when multiplied by a speci ed index, measures a counterparty s rights and obligations under a notional principal contract notional principal contract A nancial instrument that provides for payments between two parties at speci ed intervals over the life of the instrument, where one party periodically pays an amount calculated by applying a rate determined by reference to a speci ed index to a notional principal amount and the other party pays a similar amount or an amount speci ed in the terms of the instrument notional value Par value notional yield The coupon underlying a bond futures contract obligor A person who obligates himself to another party by contract.

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< xml version="1.0" > <!DOCTYPE resume [ <!ELEMENT resume (name, address, education)> <!ELEMENT address (street, city, state, zip, phone)> <!ELEMENT education (school, degree, yeargraduated)> <!ELEMENT name (#PCDATA)> <!ELEMENT street (#PCDATA)> <!ELEMENT city (#PCDATA)> <!ELEMENT state (#PCDATA)> <!ELEMENT zip (#PCDATA)> <!ELEMENT phone (#PCDATA)> <!ELEMENT school (#PCDATA)> <!ELEMENT degree (#PCDATA)> <!ELEMENT yeargraduated (#PCDATA)> ]> <resume> <name> A. Employee </name> <address> <street> 1234 My Street </street> <city> My City</city> <state> OH </state> <zip> 44120 </zip> <phone> (555) 555 5555 </phone> </address> <education> <school> Whassamatta U.</school> <degree> B.S. </degree> <yeargraduated> 1920 </yeargraduated> </education> </resume>

off-the-run bond A bond that had been out for some time, with coupon rates that may not re ect current market conditions; often less liquid than more current on-the-run bonds on-the-run Treasury An informal classi cation for the most recently issued Treasury instruments, which tend to have the greatest liquidity optimization The process of choosing the constituents of an investment portfolio, and their weights, in order to maximize a goal such as investor utility or return-risk tradeoff option A nancial instrument that conveys the right (but not the obligation) to buy or sell an underlying asset at a speci ed price (the strike or exercise price) at or before a speci ed future date (the expiration date) option-adjusted duration A measure of the duration of a CMO that takes into account the effect of a change in interest rates on prepayment rates.

P(X(tj ) < x, j = 1, . . . , n; j = k|X(tk ) = x) e (1/2)(x m(tk )) = (x)Gn (x), 2

where yi = (yi1, yi2, . . . yiT)0 , pi ( ) = (pi1, pi2, . . . piT)0 , Di = @pi ( )/@ , Vi is the working covariance matrix of yi and u ( ) is a (p + 1) 1 vector (Liang and Zeger, 1986). It should be kept in mind that, while Vi may differ from the true covariance matrix of yi, we assume that the mean of yi is correctly specified, i.e. E(yi) = pi ( ). Note that Vi may be written as Vi A2 Ri A2 , where Ai is a diagonal T T matrix with diagonal elements i i Var(yit) = pit(1 pit) and Ri is a T T working correlation matrix. Under a working independence assumption, Ri is the T T identity matrix and Equation (20.2) then reduces to X XT X XT ^ ^ u0 yit pit 0; u1 x y pit 0; 20:3 t 1 t 1 it it i2s i2s corresponding to 0 and 1, respectively. In the case of a complex survey design, denote the survey weights by {wi, i 2 s}. The survey weights {wi, i 2 s} may represent design weights {di, i 2 s} adjusted for unit non response and poststratification. We assume no wave nonresponse here. Rao (1998) proposed the following survey-weighted estimating equations (SEEI) for estimating : ^ u1w X

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