Online Appendix (not for publication)

Size: px
Start display at page:

Download "Online Appendix (not for publication)"

Transcription

1 B Onlne Appendx not for publcaton) Ths Onlne Appendx provdes some addtonal results referenced n the paper. B.1 Recoverng the equlbrum varables from the Unversal Gravty condtons In ths subsecton, we show how the unversal gravty condtons C.1-C.5 can be combned to derve equatons 6) and 7), whch can be used to solve for equlbrum prces and prce ndces up to scale. We then show how nformaton of these prces and prce ndces up-to-scale can be used to solve for the level of real output prces {p /P } S and, combned wth the numerare n C.6, to determne the equlbrum level of ncome {Y } S, expendture {E } S, and trade flows {X }, S. Fnally, we show how all other endogenous varables can be recovered up-to-scale f the equlbrum prces and prce ndces are known up to scale. B.1.1 From Unversal Gravty C.1-C.5 to Equatons 6) and 7) We frst show Unversal Gravty C.1-C.5 mply equatons 6) and 7). Combng C.1 and C.2 n partcular the gravty equaton 10)): where recall from C.2 that the prce ndex can be wrtten as: X = P E, 31) P S 32) Combnng equaton 31) wth C.4) and C.5) yelds: p Q = S P p Q 33) Fnally, we substtute C.3 nto equaton 33) to yeld: ) p p C = ) P P p p C P S 34) Note that equatons 32) and 34) are equvalent to equatons 6) and 7). Hence, C.1-C. 5 mply equatons 6) and 7), as clamed. There are two thngs to note about equlbrum equatons 32) and 34): frst, they depend only on output prces {p }, the prce ndces {P }, and exogenous model fundamentals n partcular, they do not depend on the endogenous scalar κ); second, they are homogeneous of degree zero wth respect to {p, P }, so the scale of prces and prce ndces) are undetermned. B.1.2 From Equatons 6) and 7) to endogenous varables We now show that gven a soluton to equatons 6) and 7), we can construct all endogenous varables n the models. We dvde the dervatons nto endogenous varables determned up to scale and endogenous varables for whch the scale s known gven the choce of numerare n C.6. 41

2 Suppose that we have a set of prces {p } S and prce ndces {P } S that solve equatons 6) and 7). Note that because equatons 6) and 7) are homogeneous of degree zero wth respect to {p, P } S, for any scalar α, the normalzed prces p 1 α p and prce ndces P 1 α P contnue to satsfy equatons 6) and 7). We frst solve for the real output prce. Note that for any choce of α, the real output prce {p /P } S remans unchanged, so ts level s unaffected by the unknown scalar. We now solve for quanttes. From equaton 11), the quantty n locaton does not depend on α, but t does depend on the unknown scalar κ as follows: p Q = κc. P Hence, equlbrum quanttes are only determne up-to-scale. We now solve for ncome and expendture. From C.4 and C.5 we have: E = Y = p Q. Applyng the numerare n C.6 then yelds: Y = 1 κα S S p Q = 1 S p C p P = 1 κα = S ) 1 p p C, P whch, as clamed, pns down the product of the unknown quantty scalar and unknown prce scalar. Gven κα, we can now determne the level of ncome and expendture as follows: E = Y = p Q E = Y = p C p P S p C p P ), as clamed. We now determne the level of trade flows usng equaton 31): X = P E X = k S k p k ) p ψ p C P ) ) ψ k S p pk. kc k P k Other than real output prces {p /P } S, ncome {Y } S, expendture {E } S, and trade flows 42

3 {X }, S, all other endogenous varables are determned only up-to-scale, as they depend ether on the prce scalar α.e. output prces p, prce ndces P, blateral prces p = τ p, and the quantty traded Q = X /τ p ) or the quantty scalar κ.e. quanttes Q ). B.2 Proof of Theorem 1 part ) We frst provde a general mathematcal formulaton to ncorporate non-nteror solutons. Let the equlbrum be a duple p, Q ) R N + R N + such that for all S, Q = 1 1 k S k p k p Q 35) p, Q ) F p, Q) 36) where F s a supply condton, whch mght be a correspondence. The fact that F mght be correspondence allows us to extend the framework to allow for non-nteror solutons). In partcular, we defne F as follows: We say p, Q ) F p, Q) f and only f [ ) ] ψ p sgn ψ) Q κ 0 37) P p) p Q = κ f Q > 0, 38) P p) and where 0 0) s defned as 0. That s, f Q = 0, then we replace C.3 wth an nequalty. For example, n an economc geography model, nequalty constrant 37) corresponds to welfare equalzaton. If there are people lvng n locaton, then Q s gven by equalty 38). If not, then the welfare lvng n locaton should be lower than one obtaned n other places, whch s represented as the nequalty 37). As we mentoned n Secton 3, we restrct our attenton to non-trval equlbra where there s postve producton n at least one locaton. To show that all non-trval) equlbra are nteror, t then suffces to show that f some locatons produces nothng, then all other locatons must also produce nothng. Suppose that Q l = 0 for some l S. Then from equaton 35) for l: 0 = l 1 l k S k p k } {{ } 0 p Q, 39) whch n turn mples that for all S, l 1 l p Q = 0, 40) g where g = k S k p k. Note that there are two reasons why equaton 40) s zero for all ; ether 1) ; or 2) for all S, l = 0. We wll prove a contradcton n both cases. p Q g 43

4 Frst assume that 1) 1 l = 0, whch f > 1 mples that p l =. Whle p l, Q l ) =, 0) satsfes equaton 39), t does not satsfy equaton 36). To see ths, note: 0 = Q < κ p g 1 ψ =, whch contradcts wth equaton 37) snce ψ 0. Therefore p l needs to be fnte, p l <. Now assume that 2) for all S, p Q l g = 0. Snce the prce for country l s fnte, equaton 40) s reduced to p Q l = 0 g for all S. An equvalent expresson s that for all countres connected wth l, S l = {k S; τ lk < }, p Q = 0 or g =. 41) Fx any country S l. Suppose that p, Q > 0 Then equaton 41), g =. Then for all p, Q ) R + R f ψ 0 we have = κ p g 1 ψ Q = 0, whch s a contradcton. Therefore n order to satsfy equaton 41), p or Q needs to be zero. Suppose that p = 0. Then we have 0 = κ p g 1 ψ Q. If Q > 0, then C. 3). Therefore, Q = 0. Therefore Q needs to be zero for all S l. So far, we have shown that f Q l = 0 then the connected countres S l produce nothng, Q = 0. Because of strong connectedness, any country n s connected wth l through thrd countres. Therefore, by repeatng the argument along wth the chan, we have Q n = 0 for all n S. As a result, f 1, and ψ 0 then all equlbra are nteror, as clamed. B.3 Quas-symmetrc trade frctons In ths subsecton, we show that when trade frctons are quas-symmetrc, then balanced trade mples that the orgn and destnaton fxed effects of the gravty trade flow expresson are equal up to scale. We frst formally defne quas-symmetry. We say that the set of trade frctons {τ }, S are quas-symmetrc f there exsts a set of orgn scalars { τ A } S RN ++, destnaton scalars { } τ B S RN ++, and a symmetrc matrx { τ }, S where τ = τ for all, S such that we can wrte: τ = τ A τ B τ, S. Loosely speakng, quas-symmetrc trade frctons are those that are reducble to a symmetrc component and exporter- and mporter-specfc components. Whle restrctve, t s mportant to 44

5 note that the vast maorty of papers whch estmate gravty equatons assume that trade frctons are quas-symmetrc; for example Eaton and Kortum 2002) and Waugh 2010) assume that trade frctons are composed by a symmetrc component that depends on blateral dstance and on a destnaton or orgn fxed effect. Combnng the unversal gravty condtons C. 1 and C. 2 allows us to wrte the value of blateral trade flows from to as: X = P E, whch we now re-wrte as: where we call γ effect. X = κ γ δ, 42) the orgn fxed effect and δ P E = C P ψ p 1+ψ the destnaton fxed Proposton 1. If trade frctons are quas-symmetrc, then n any model wthn the unversal gravty framework, the product of the equlbrum orgn fxed effect and the orgn scalar wll be equal to the product of the equlbrum destnaton fxed effects and the destnaton fxed effect up to scale,.e.: for some scalar λ 0, τ A ) γ = λ τ B ) δ S. Proof. We frst note that market clearng condton C.4 and balanced trade condton C.5 together mply that: S X = S X S. Combnng ths wth the gravty expresson 42) and quas-symmetry mples: κ γ δ κ γ δ }{{}}{{} =X = ) τ A γ S ) τ B = δ S X τ τ τ A τ B ) γ ) δ = S k S τ B τ k ) δ τ B k ) δk τ A τ B ) γ ) δ. It s easy to show that τ A ) γ = 1 s a soluton to ths problem for any kernel. From the Perron- τ B ) δ Frobenus theorem, the soluton s unque up to scale. Therefore we have: ) τ A ) = λ τ B δ S, 43) as requred. Proposton 1 has a number of mportant mplcatons. Frst, Proposton 1 allows one to smplfy the equlbrum system of equatons 6 and 7 nto a sngle non-lnear equaton when ψ: p 1+ψ+ ψ ) = λ) ψ C ) ψ S ) τ A 2 ψ τ B ) ψ ψ τ A ) p, S, 44) whch smplfes the characterzaton of the theoretcal and emprcal propertes of the equlbrum. 45

6 Notce that λ s an endogenous scalar. Snce 44) holds for any locaton S, λ s expressed as λ ψ = Substtutng above expresson, we obtan: S τ A τ B ) 1+ψ+ ψ ) 2 ψ ψ C. ) 1+ψ+ ψ ) 1+ψ+ ψ = S τ A τ B ) 2 ψ S τ A τ B ψ C ) 2 ψ ψ C. Notce that the system s now homogeneous degree 0. Therefore, f / { 1 2, ψ, 0}, then we can normalze λ = 1 wthout loss of generalty. Second, by showng that the orgn and destnaton fxed effects are equal up to scale, Proposton 1 provdes offers an analytcal characterzaton of the equlbrum. For example, gven the defnton of the orgn and destnaton fxed effects, Proposton 1 can equvalently be expressed as: p P τ B τ A E 1, 45).e. there s a log-lnear relatonshp between output prces, the prce ndex and total expendture n a locaton. Thrd, t s straghtforward to show that quas-symmetry mples that equlbrum trade flows wll be blaterally symmetrc,.e. X = X for all, S, allowng one to test whether trade frctons are quas-symmetrc drectly from observed trade flow data. Fnally, we should note that the results of Proposton 1 have already been used n the lterature for partcular models, albet mplctly. The most promnent example s Anderson and Van Wncoop 2003), who use the result to show the blateral resstance s equal to the prce ndex. 36 To our knowledge, Head and Mayer 2013) are the frst to recognze the mportance of balanced trade and market clearng n generatng the result for the Armngton model; however, Proposton 1 shows that the result apples more generally to any model wth quas-symmetrcal trade frctons n the unversal gravty framework. B.4 Proofs of the lemmas used n Theorem 1) There are 4 lemmas whch are not proven n the paper. In ths secton, we dscuss them carefully. Before provng these lemmas, we dscuss how we use them n the proof. In the proof, we show a fxed pont for the scaled system, not the actual system. Therefore t needs to be shown that there exsts a fxed pont for the actual system, whch s shown n Lemma 1. Then we argue that the soluton we obtan s strctly postve, whch s guaranteed by Assumpton 1. We emphasze the connectvty assumpton s crucal here. These two lemmas are used n Part ) Theorem 1. Part ) shows that there exsts an unque soluton. Durng the proof, we argue that 26 should hold wth strct nequalty. Agan the connectvty allows us to show ths result Lemma 3). After 36 The result s also used n economc geography byallen and Arkolaks 2014) to smplfy a set on non-lnear ntegral equatons nto a sngle ntegral equaton. 46

7 establshng ths strct nequalty, we follow the argument by Allen et al. 2014), whch requres that the largest absolute egenvalues for A are less than 1. Snce A s a 2-by-2 matrx, we can compute the egenvalues by hand and show that one of them s exactly 1, and the other s less than 1 f the condtons n Part ) are satsfed. Lemma 1. Suppose that z solves 22). Then there exsts ẑ solvng 21). Proof. Frst t s easy to show 37, S K C 1 C x a 11 y a 12 = K x a 21 y a ), S Guess a soluton ) x ) ẑ = t = 1 ) x ) ŷ ) t 1, 49) y ) ) where t =, S K C 1 C x a 21 y a a 11 a 12 ) =, S K x a 21 y a a 21 a Then t s easy to verfy that 49) solves 21); n partcular, note that x = t 1 S K C 1 C x a 11 y a 12, S K C 1 C x a 11 y a = t 1 a 11 a 12 S K C 1 C x ) a 11 ŷ a 12 12, S K C 1 C x a 11 y a 12 = S K C 1 C x a 11 ŷ a 12. We can also show that the second equatons n 21) are also solved n the same ven: S ŷ = t K x a 21 y a 22, S K x a 21 y a = t 1 a 21 a 22 S K x a 21 ŷ a 22 22, S K x a 21 y a 22 = S K x a 21 ŷ a 22. The above two equatons confrm that x and ŷ s a soluton to 21). 37 To see ths, multply C x a21 y a22 = C, to the frst equatons of 22) and sum over ; C p 1+ψ P ψ = Also multply C x a11 y a12 = C P ψ p 1+ψ S K C x a21, K C 1 y a22 C x a11 x a11 y a12 y a12. 46) to the second equatons 22) and sum over ; S S K C x a21 y a22 x a11 y a12. 47) C p 1+ψ P ψ = S, S K x a21 Notce that the LHS s the same as one n 46). Also the numerator of the RHS n 46) s the same as one n 47). Therefore the followng double sum terms should be the same:, 38 Notce that a 11 + a 12 = a 21 + a 22. K C 1 C x a11 y a12 = S, S y a22 K x a21 y a22. 47

8 Lemma 2. If {τ }, satsfes Assumpton 1, then the fxed pont for 22) s strctly postve. Proof. We need to consder four dfferent cases for the combnatons of a 11, a 12 satsfyng dfferent nequaltes. We wll consder the case a 11, a 12 > 0 snce the logc n the other cases s the same. We proceed by contradcton. Suppose that there s a soluton x to equaton 22) such that for some S x = 0. Consder an arbtrary locaton n and consder a connected path, K c n K π1... K πmn > 0 for some m ). Then, from the frst of equatons n 21) notce that x = K x a 11 y a 12 K π1 S }{{} 0 x a 11 π 1 y a 12 π 1. Note that K π1 s strctly postve due to ). Then ether x n or y n or both are zero f a 11 and a 11 > 0. Ifx n = 0 ths argument holds for anyn so ths s a contradcton wth the non-zero equlbrum proved above. Else f y n = 0 we can repeat the argument the second of the equatons n 21) to establsh another contradcton. Notce that f ether of α 11, α 12 = 0 a contradcton s also easy to establsh. Lemma 3. Equaton 26 holds wth strct nequalty. To that end, defne the set of drectly connected countres to each locaton S as S c { S : K > 0}. Then notce that equaton 24) combned wth our equalty assumpton on equaton 26) yelds x = 1 x ) α11 ) α12 ) α11 ) α12 K C 1 x y C x ) α 11 ŷ ) α 12 x y = max max. x x ŷ S x S ŷ S c Notce that gven that ˆx s a soluton, ths mples that the followng has to be true for all S c ) α11 ) α11 ) α12 ) α12 x x y y = max = max. x S x ŷ S ŷ Now notce that f α 11 0 then for all n S c,x / x = x n / x n. However, because of C. 1, we assume that there exsts an ndrectly connected path from any locaton to any other locaton, so that repeatng ths argument for all and usng the ndrect connectvty we can prove that x / x = x n / x n for all, n S.e. the solutons are the same up-to-scale, a contradcton. Lemma 4. If, ψ 0 or, ψ 1, the egenvalue for A s λ = ψ ψ, 1, and ψ ψ < 1. Proof. Notce that A = 1+ψ 1+ψ+ 1+ψ ψ+ ψ 1+ψ+ = 1+ψ 1+ψ+ 1+ψ ψ+ ψ 1+ψ+ Then we can solve the followng characterstc functons ) 1 + ψ λ ψ + + ψ λ ψ ψ 1 + ψ ψ ψ ψ + 48 ). 1 + ψ + = 0.

9 Then We need to show that ψ 1++ψ λ = ψ ψ, 1. < 1. To show t, t suffces to show g = ψ ψ > 0 Suppose that, ψ 0. Then g s strctly postve as follows: g = ψ ψ Suppose that, ψ 1. Then g s gven by If ψ, then If ψ, then whch completes the proof ψ + ψ ) = 1 > 0. g = 1 ψ ψ. g = 1 ψ + ψ = 1 2ψ 1. g = 1 ψ + ψ = 1 2ψ 1, B.5 Lemmas and Proposton used n Theorem 2 ) 39 In ths secton, we prove the lemma and proposton used n Theorem 2 ). Lemma 5. If, ψ 0 or, ψ 1, then A has strctly postve dagonal elements and s dagonal domnant n ts rows; namely, for all S A > 0, 50) A > A. 51) S Proof. Recall that A matrx s and from Lemma 4, A = Y + ψ 1 + ψ + X, ψ ψ < A smlar argument s found n Johnson and Smth 2011). 49

10 Then the dagonal elements for A are postve; for all S, Also, for all S, whch s equaton 51). A l S A l A = Y + ψ 1 + ψ + X = Y ψ 1 + ψ + X > Y X 0. = Y + ψ 1 + ψ + X ψ }{{} 1 + ψ + X l l S >0 =Y + ψ 1 + ψ + X ψ 1 + ψ + Y X ) = 1 ψ 1 + ψ + Y ψ ψ + + ψ 1 + ψ + X > 0, }{{}}{{} >0 0 The next proposton plays a crucal role n the proof for Theorem 2 ). Proposton 2. If A has strctly postve dagonal elements and s domnant of ts rows, then for all, A 1 > A 1 > 0. Proof. The co-factor expanson of A 1 s 40 A 1 A 1 = det A [S ]) 1)+ det A [S, S ]) det A) det T ) = det A), where T s defned as follows: 40 Remember T = A + 0,, 0, A }{{}}{{}, I 0,, 0 }{{}. N 1) N 1 N N ) A 1 = 1) + det A [N, N ]). det A) 50

11 T s a prncpal component of T : T = T [S, S ]. If a matrx C has postve dagonal elements, and s dagonally domnant of ts rows, then det C) > Then f T has such propertes, then det T ) det A) > 0 snce A s assumed to have these propertes. Thus t suffces to show that T has postve dagonal elements and s domnant of ts rows. By constructon of T, t suffces to show A kk > 0 k S 52) A kk + A k > 0 k = 53) A kk > A kl + 1 l= A k k S 54) l S k A kk + A k > l S k A kl k =. 55) Frst we show equaton 52) and equaton 53). snce A has a strctly postve dagonal, for all k S, A kk > 0, whch s equaton 52). Also snce A s dagonal domnant, A + A > l A l + A A + A 0, whch s equaton 53). Second, we show equaton 54) and equaton 55). Fx k N. Snce A s dagonally domnant, A kk > = l S k A kl l S k l S k = l S k A kl + A k + A k A kl + A k + A k trangle nequalty) A kl + 1 l= A k, whch s equaton 54). Fx k =. Snce A has postve dagonal elements, and s dagonally 41 See also Theorem 3 of Evmorfopoulos 2012). 51

12 domnant, whch s equaton 55). A kk + A k A kk A k = A kk A k = l S k = l S k A kk A kl + A k A k A kl, l S k A kl A k B.6 Exstence and Unqueness usng Gross Substtutes Methodology a la Alvarez and Lucas 2007)) In ths subsecton, we prove the exstence and unqueness of an equlbrum n our unversal gravty framework usng the gross substtutes methodology employed by Alvarez and Lucas 2007). As we show below, the suffcent condtons here are stronger than we provde n Theorem 1 above. Proposton 3. Consder any model wthn the unversal gravty framework. If > ψ > 0 and τ 0, ) for all, S, then the excess demand system of the model satsfes gross substtutes and, as a result, the equlbrum exsts and s unque. Proof. Recall the equlbrum condtons of the unversal gravty framework from equatons 6) and ) p p C = P S P = S P p p C S 56) P S 57) Substtutng equaton 57) nto 56) yelds a sngle equlbrum system of equatons that depends only on the output prces n every locaton: p 1++ψ S ψ C = S C p 1+ψ We defne the correspondng excess demand functon as: Z p) = 1 p S k S C k C p 1+ψ 1 l S lk βp l) k S k p k k S βp k p 1+ψ k p k S S ψ C, 58) 52

13 wherep s defned by equaton 57).Ths system wrtten as such needs to satsfy 6 propertes to be an excess demand system and the gross substtute property to establsh exstence and unqueness. The sx condtons are: 1.Z p) s contnuous forp R+ N ) 2.Z p) s homogeneous of degree zero. 3.Z p) p = 0 Walras Law). 4. There exsts ak > 0 such thatz p) > k for all. 5. If there exsts a sequence p m p 0, where p 0 0 and p 0 = 0 for some, then t must be that: max {Z p m )} 59) and the gross-substtute property: 6. Gross substtutes property: Zp ) p k > 0 for all k. We verfy each of these propertes n turn. Property 1 s trval gven equaton 58) for excess demand. To see property 2, consder multplyng output prces by a scalar β > 0, whch mmedately yelds Z βp) = Z p).as requred. Property 3 can be seen as follows: Z p) p = = S Z p) p = = S k S C k S 1 l S lk p l C p 1+ψ p ψ k k S k p k p 1+ψ S ψ C =0, as requred. Property 4 can be seen as follows: snce 1 p Z p) = 1 p S k S C k Z p) > Q > Q 1 k S C k C l S lk βp l) βp k p 1+ψ ) k S ψ k p k Q l S lk βp l) = βp k S C p 1+ψ ) k S ψ k p k > 0 for all p 0 and Q Q from C. 3. Property 5 can be seen as follows: consder any p R N + ) such that there exsts anl S wherep l = 0 and anl S wherep l > 0. Consder any sequence of output prces such that p n p asn. Then we need to show that: max S Z p). 53

14 To see ths note that: max Z p n ) = max S S max Z p n p ) > max S, S 1 p S τ p ) C p 1+ψ ψ k S τ kp k ) ) p Hence, f t s the case that max, S p k S C k C p ψ k S C k p l S lk p l k S k p k l S lk p l p ψ k p ψ k ) C p ψ k S ψ k p k k S C k l S lk p l p ψ k Q. s bounded below t, t must be that max S Z p n ) as well. Note that: Q =, then because max S Z p n ) p max, S p C p ψ k S C k ) k S ψ k p k l S lk p l p ψ k p > max, S p C k S C k > C mn l S p ψ) l, p ψ k S k p mn ) ) ψ l S lk pmn ) ) = ψ p max where p mn mn l S p l,p max max l S, and C C k S ψ k p mn ) ). Snce k S C k l S lk pmn ) p max as n, then we have max S Z p n ) > ψ > 0 and there exsts anl S such that p n l as well. Fnally, we verfy gross-substtutes. Wthout loss of generalty, we dfferentate only the bracketed term as the term outsde the bracket wll be multpled by zero snce the bracket term s equal to zero n the equlbrum). We have: Z p) p = p S = 1 + ψ) ψ) 1 C p 1+ψ C l S p ψ l k S C l k S k p k k p k p ψ l k S + kl k p 1+ψ S 1 + ψ 1 p 1+ψ ψ C S ψ 1 > 0 because > ψ > 0 and prces, trade frctons, and supply shfters C l are strctly postve. Because propertes 1-6 hold, by Propostons 17.B.2, 17.C.1 and 17.F.3 of Mas-Colell et al. 1995), the equlbrum exsts and unque. Note that n the case where ψ > > 0 whch s the orderng we fnd when we estmate the gravty constants n Secton 5 Theorem 1 stll proves exstence and unqueness of the equlbrum. The followng example shows that gross substtutes may not be satsfed n ths case. 54

15 Example 1. Gross substtuton) Consder the three locaton economy. Take p 3 as the numerare The gross substtute s volated f there exsts p 1 such that Z 1 p 1, p 2, 1) s not monotonc w.r.t. p 2. Consder the followng parameter values:, ψ) = 2, 5) τ = 1 for, {1, 2, 3} C =.9,.6,.1) T. Fgure 12 shows that wth these parameter values, Z 1 p 1, p 2, 1) s not monotonc w.r.t. p 2 when p 1 =.5. B.7 Examples of multplcty n two locaton world In ths subsecton, we derve the equlbrum condtons of a two locaton world and provde examples for dfferent combnatons of the gravty constants.e. the demand elastcty and supply elastcty ψ). We frst derve equatons for the demand and supply of the representatve good n each locaton as a functon of parameters and prces n all other locatons. Combnng C. 2 aggregate demand) and C. 3 market clearng) yelds the followng aggregate demand equaton: Q d = p 1+) S k p Q d k p, 60) k where we denote the quantty of the representatve good demanded n locaton as Q d. Smlarly, C. 3 aggregate supply) yelds the followng aggregate supply equaton: Q s = κc p S p1 p 2 ) +1 p1 p 2 ) +τ, 61) where we denote the quantty of the representatve good suppled n locaton as Q d. Now consder the two-locaton case.e. S {1, 2}) where τ 12 = τ 21 = τ 1 and C 1 = C 2 = 1. Dvdng Q d 1 by Qd 2 usng equaton 60) delvers the followng relatve demand equaton: ) p1 +1 ) p Q d ) ) 2 1+) p1 +τ p 1 p 2 Qd 1 + Q d 1 p1 2 p Q d = 2 ) ) 62) 2 p 2 p 1 p 2 Qd Q d 2 Smlarly, dvdng Q s 1 by Qs 2 delvers the followng relatve supply equaton: Q s 1 Q s 2 = p1 p 2 ) ) ψ p1 p ) p1 p 2 + ψ 63) Note that gven the trade frcton τ and gravty constants, the relatve demand and relatve supply 55

16 can be solved solely as a functon of relatve output prce p 1 p 2 usng equatons 62) and 63), allowng us to analytcally characterze the equlbra usng standard relatve) supply and demand curves. Fgure 3 depcts example equlbra possble for dfferent combnatons of gravty constants; the ponts where the two curves ntersect are possble equlbra. The top left fgure shows that when the supply and demand elastctes are both postve correspondng to a case where the relatve aggregate supply s ncreasng and the relatve aggregate demand s decreasng), there s a unque equlbrum. The top rght fgure shows that when the supply elastcty s postve but the demand elastcty s negatve, both the relatve aggregate supply and demands are ncreasng, potentally resultng n multple equlbra. Smlarly, the bottom left fgure shows that when the supply elastcty s negatve and the demand elastcty s postve, both the relatve aggregate supply and demand curves are decreasng, also potentally resultng n multple equlbra. Fnally, the bottom rght fgure shows that when both the supply and demand elastctes are negatve and sutably large n magntude, the relatve aggregate supply curve s downward slopng and the relatve aggregate demand curve s upward slopng, allowng for a unque equlbra albet one wthout much economc relevance). These examples are consstent wth the suffcent condtons for unqueness presented n Theorem 1. B.8 Tarffs n the unversal gravty framework In ths subsecton, we show how one can use the tools developed above to analyze the effect of tarffs n a smple Armngton trade model. Because tarffs ntroduce an addtonal source of revenue, they are are not strctly contaned wthn the unversal gravty framework. However, t turns out that the equlbrum structure of an Armngton trade model wth tarffs s mathematcally equvalent to the equlbrum structure of the unversal gravty framework. As a result, we can apply Theorems 1 and 2 almost mmedately to the case of tarffs n ths model. To see ths, consder a smple Armngton trade model wth N locatons. 42 Each locaton S s endowed wth ts own dfferentated varety and L workers who supply ther unt labor nelastcally and consume varetes from all locatons wth CES preferences and an elastcty of substtuton σ. Suppose that trade s subect to technologcal ceberg trade frctons τ 1 and ad-valorem tarffs t 0. Defne t 1 + t. Then we can wrte the value of trade flows from to excludng the tarffs) as: X = τ 1 σ t σ Aσ 1 w 1 σ P σ 1 E, 64) where A s the productvty n locaton S, w s the wage, P s the deal Dxt-Stgltz prce ndex, and E s expendture. Income n locaton from trade s equal to ts total sales excludng tarffs): Y = S X. 65) Total ncome and hence expendture) also ncludes the revenue earned from tarffs T : E = Y + T, 66) 42 We consder an Armngton model n order to have an explct welfare functon, the results that follow wll hold for any general equlbrum model where the aggregate supply elastctyψ = 0. 56

17 where tarff revenue s equal to the blateral tarff charged on all trade beng sent 43 : T = S t X. 67) The total expendture by consumers n locaton s also equal to ts total mports plus the tarffs ncurred: E = ) 1 + t X. 68) S Combnng equatons 66), 67), 68), we can demonstrate that trade flows are balanced: E = S 1 + t ) X Y + S t X = S 1 + t ) X Y = S X 69) Fnally, total expendture s equal to the payment to workers plus tarff revenue: E = w L + T Y = w L 70) Defne K τ 1 σ t σ as the blateral kernel, B A L as the ncome shfter, γ A σ 1 w 1 σ as the orgn fxed effect, δ P σ 1 E as the destnaton fxed effect, and α 1 1 σ. Combnng equatons 65), 69), and 70) yelds the followng system of equlbrum equatons: w L = S X B γ α = S K γ δ 71) w L = S X B γ α = S K γ δ. 72) Equatons 71) and 72) can be ontly solved to recover the equlbrum {γ } S and {δ } S ; gven {γ } S and {δ } S, n turn, we can solve for all endogenous varables, as wages can be wrtten 1 1 σ ) 1 as w = γ A, the prce ndex can be wrtten as P = S τ 1 σ t 1 σ 1 σ γ, expendture can ) be wrtten as E = δ S τ 1 σ t 1 σ γ, and real expendture can be wrtten as W E P = δ S τ 1 σ ) σ t 1 σ σ 1 γ. As we note at the begnnng of Secton 3, ths equlbrum system s 43 If we had nstead supposed that tarffs are only leved on goods that actually arrve, we would havet = t τ X, whch does not change the followng analyss n any substantve way. 57

18 dentcal n mathematcal structure to the unversal gravty equlbrum equatons 6 and 7. Hence, Theorem 1 apples drectly wth exstence as long as σ 0 and unqueness as long as σ 1). Moreover, a smlar methodology as employed n Theorem 2 can be used to determne how the equlbrum varables γ and δ respond to shocks that alter the kernel K be they due to changes n ceberg trade frctons or tarffs). In partcular: ln γ ) l = X A + ln K l, + A+ N+l, c 73) ln δ ) l = X A + ln K N+l, + A+ l, c, 74) where à 1, s the, element of the 2N 2N matrx the pseudo) nverse à 1 : 44 à 1 = σ 1 σ Y 1 1 σ Y XT X ) 1, 75) Y Because all endogenous varables n the model are smple functons {γ } S and {δ } S, one can apply equatons 73) and 74) to mmedately derve any elastcty of nterest, e.g. the effect of welfare n locaton l from changng the tarffs mpose on goods comng from. B.9 Global shocks In ths subsecton we show that the exact hat algebra poneered by Dekle et al. 2008) and extended by Costnot and Rodrguez-Clare 2013) can be appled to any model n the unversal gravty framework to calculate the effect of any possbly large) trade shock. Note that Secton 4 nstead showed how to calculate the elastcty of endogenous varables to any trade frcton shock). We show that the key takeaway from Secton 4 holds for all trade shocks: Gven observed data, all the gravty models wth the same gravty constants mply the same counterfactual predctons for all endogenous varables.e. output prces, prce ndces, nomnal ncomes, real expendtures, and trade flows). Consder an arbtrary change n the trade frcton matrx {τ } S S. In what follows, we denote wth a hat the rato of the counterfactual to ntal value of the varable,.e. ˆx xcounterfactual. x ntal The followng proposton provdes an analytcal expresson relatng the change n the output prce and the assocated prce ndex to the change n trade frctons and the ntal observed trade flows: Proposton 4. Consder any gven set of observed trade flowsx, gravty constants andψ, and change n the trade { frcton } matrx τ. Then the percentage change n the exporter and mporter shfters, {ˆp } and ˆP, f t exsts, wll solve the followng system of equatons: p 1++ψ P ψ = S X P Y p p and P = P S X E ) ˆ ˆ, S 76) Proof. We frst note that equlbrum equatons 10) and 7) must hold for both the ntal and 44 The psuedo-nverse can be calculated smply by removng the frst row and column and takng the nverse; see footnote

19 counterfactual equlbra. Takng ratos of the counterfactual to ntal values yelds: p 1++ψ P ψ = P = ) ) S τ P p p C P S S τ P p p C ) p S ) P, S S where we denote the counterfactual equlbrum varables wth a prme and the ntal equlbrum varables as unadorned. Note that from the gravty equaton 10) and C. 3 - C. 5) we have X = ) P p p ψ ) p ψ C P, where p C P = E, so that the above equatons become: p 1++ψ P ψ = P = ) S τ S τ P p ) P ) p p C P S S X ) p 1 E S X, S Fnally, note that from C. 2 and C. 4 we have E = S X and Y = S X, respectvely. Then usng our defnton ˆx xcounterfactual x ntal as requred. p 1++ψ P ψ P = S = S x counterfactual X Y X E = ˆx x ntal ) ˆ ˆP ˆp p S P ) ˆ ˆ S, we have: Note that equaton 76) nherts the same mathematcal structure as equatons 6) and 7). As a result, part ) of Theorem 1 proves that there wll exst a soluton to equaton 76) and part ) of Theorem 1 provdes condtons for ts unqueness. B.10 Identfcaton In ths subsecton, we show how one can always choose a set of blateral trade frctons to match observed trade flows for any choce of gravty constants, own trade frctons, and supply shfters. We frst state the result as a proposton before provdng a proof. Proposton 5. Take as gven the set of observed trade flows {X }, an assumed set of supply shfters {C }, an aggregate scalar κ, and own trade frctons {τ }, and the gravty constants and ψ. Then there exsts a unque set of trade frctons {τ }, output prces {p }, prce ndces {P }, and output {Q } such that the followng equlbrum condtons hold: 59

20 1. For all locatons S, ncome s equal to the product of the output prce and theoutput: Y = p Q 2. For all locaton pars, S, the value of trade flows from to can be wrtten n the followng gravty equaton form: X = P E 3. For all locatons S, output satsfes the followng supply condton: p Q = κc P Proof. Frst, note that the ncome Y = S X, expendture E = S X, and own expendture share λ X E, are all mmedately derved from the observed trade flow data. Second, let us defne our unknown parameters and endogenous varables as functons of data and known parameters. The trade frctons are defned follows: τ = τ Y Y for all, S such that. The output prces are defned as ) λ λ C C p = Y λ τ ) τ X τ /κc for all S. Gven the output prces and trade frctons, the prce ndex s defned as: for all S, P = S 1. X ) 1 Fnally, the output n each locaton s defned as: for all S, p Q = κc. P It s frst helpful to note that gven the above defntons of the trade frctons and output prce ndces, we have the followng convenent relatonshp between own expendture shares and prces: λ = ) τ P 60

21 To see ths, note that we can wrte: Y /C ) λ τ λ = X E = p = p = ) τ P p S ) X E X p = S p p = S = S E S ) ) Y λ τ Y λ X E X E X E S ) Y /C ) λ τ ) ) C ψ τ X Y /C ) λ τ ) Y /C ) λ τ p ) p C τ p X ) 1 ) E = S X, whch s the defnton of E. We now confrm each of the three equlbrum condtons. To see that ncome s equal to the product of the output prce and the output, we wrte: p Q = Y p Q = Y ) λ τ ψ ) /κc Q ) 1 p κc Q P p Q = Y Q Q p Q = Y, as requred. To see that the value of trade flows can be wrtten n the gravty equaton form, we wrte the gravty equaton as follows: P E = ) Y λ τ Y λ ) ) C ψ τ X C ) P E Y /C ) λ ψ = X τ ψ p Y /C ) λ ψ τ ψ p τ ) X p X ) 1 ) P E P E 61

22 Recall from above that we have the followng relatonshp between prces and own expendture shares: ) λ = τ P so that: P E = X Y ) p P C ) Y ) p P C ) p Furthermore, recall that we have defned our quanttes as follows: p Q = κc, P p ) p X P E whch mples that: P E = X Y /Q ) Y /Q ) ) p p ) p X P E We have shown above that p Q = Y, so that we have: P E = X p X P E We clam that ths mples that observed trade flows are explaned by the gravty equaton,.e.: To see ths, suppose not. Then we have X = P E P E = X p X P E but X P E. Then wthout loss of generalty we can wrte X = P E ε, where ε 1. P E = ) P E ε 1 = ε ε ε = ε ε S p p P E ) P E ε whch then mples that we have: X = P E ε 62

23 however, we know that: S X = E S P E ε = E S S = 1 ε ε = 1, whch s a contradcton. Hence, the observed trade flows are explaned by the gravty equaton. Fnally, we note that the thrd equlbrum condton trvally holds by the defnton of Q : p Q = κc. P Hence, gven our defntons, we have found a unque set of trade frctons {τ }, output prces {p } S, prce ndces {P } S, and output {Q } S such that the equlbrum condtons hold for any set of observed trade flows {X }, S, an assumed set of supply shfters {C } S and own trade frctons {τ } S, and the gravty constants, ψ). B.11 Real output prces, welfare, and the openness to trade In ths secton, we explore the relatonshp between the real output E /P and real output prce p /P n the unversal gravty framework and the welfare n a number of semnal models. We then show how the real output prce n the unversal gravty framework relates to the observed own expendture share. Combnng the two results allow ones to wrte the welfare n each of these models as a functon of observed own expendture share, as n Arkolaks et al. 2012a). B.11.1 Real output prces and welfare In ths subsecton, we provde a mappng between real output prces and the welfare of a unt of labor for the trade ntroduced and the economc geography model n Secton 2. The trade model In the trade model, the output prce p s w ζ P 1 ζ /A. As a result we have the welfare of each worker Ω can be expressed as a functon of the real output prce n the unversal gravty framework as follows: w P = p A P 1 γ ) 1 ζ } {{ } =w 1 = A P 1 γ p P ) 1 ζ. Or equvalently, we can express the welfare n terms of the supply elastcty. w = A 1+ψ P p P ) 1+ψ. 63

24 The economc geography model In the economc geography model, the welfare s w P u,and the prce p s. Therefore the welfare s w A L a Ω = A u L a+b p Welfare equalzaton and the labor market clearng condton mples S P ). Ω = L ) [ a+b [ )] 1 ] a+b) p a+b A u. P B.11.2 Real expendture, real output prces and the openness to trade In ths subsecton, we show we can express real expendture and real output prces n any model wthn the unversal gravty framework as a functon of openness to trade and the gravty constants, as n Arkolaks et al. 2012a). We begn by defnng λ X E can express the real output prce p P as locaton s own expendture share. From equaton 10), we n a locaton as a functon of ts own expendture share: X = p k S p k 1 E = = λ. 77) P Moreover, gven C. 3, C. 4 and C. 5, we can wrte total real expendture W E P ts own expendture share as well: as a functon of W = E W = W = P p P p P ) Q ) ) p κc P Combnng equatons 77) and 78) yelds: ) 1+ψ p W = κc. 78) P W = κc λ ) 1+ψ. Note that a postve aggregate supply elastcty ψ > 0) ncreases the elastcty of total real expendture to own expendture share, thereby amplfyng the gans from trade. Note too that the 64

25 dervatons above mply that: ) ln W ln p P = ψ + 1) + ln κ, ln τ ln τ ln τ.e. we can recover the elastcty of the total real expendture to-scale) to the trade frcton shock from the elastcty of the real output prce to the trade frcton shock by smply multplyng by ψ + 1. B.12 Addtonal Fgures 65

26 Fgure 3: Examples of multplcty and unqueness n two locatons a) Postve supply and demand elastctes b) Postve supply elastcty, negatve demand elastcty c) Postve demand elastcty, negatve supply elastcty 5 d) Negatve supply and demand elastctes both 1) Notes: Ths fgure shows examples of relatve supply curve and relatve demand curves for a two locaton world for dfferent combnatons of supply and demand elastctes; see Secton B.7 for a dscusson.

27 Fgure 4: Correlaton between observed ncome and own expendture shares and the equlbrum values from the gravty model Income log) Observed JPN HKG DEU FRA GBR SGP IDN THA KOR ITA TWN NLD MYS BEL CHE CHN ESP PHL IND SWE NOR AUT DNK BGD FIN POL GRC PRT IRL RUSZAF VNMTUN AUS BGR CZE HUN NGA LKA IRN EGY NZLPAK TUR MLT SVK SVN MUS HRV KHM ROU TZA CYP UGA MAR UKR BLRLTU KAZ MOZ LVA EST MMR AZE ALB MDG ZMBBWA SENLAO ARM ETH GEO MWI ZWE KGZ LUX BRA USA VEN MEX CAN COL PER ECU CRI GTM PAN ARG BOL NICPRY URY CHL Predcted Observed IDN MYS SGPTHA PHL KHM Own expendture share log) BGD ALB BGR GTM HKG JPN PAN ARM GBR LAO CHE DNK NLD LKA GRC PAK PRT COL PER SVN TZA UGA HRV ITA ESP EGY NIC KOR POL NORFRA BOL AUS BRA CRIGEO ECU CYP DEU FINLTULVA VEN NZL SEN IND KGZ ZAF SWE USA ZMB ETH AUT CZE BLR MEX IRN MOZ MAR MUS SVK ROU PRY URY TUN TURCHL ARGTWN MDG AZE CAN HUN CHN MMR KAZ MWI RUS UKR BWA VNM BEL EST ZWE MLT IRL LUX NGA Predcted Notes: Ths fgure shows the relatonshp between the observed and predcted ncome and own expendture shares, respectvely. The predcted ncomes and own expendture shares are the equlbrum values from the general equlbrum gravty model where blateral frctons are those estmated from a fxed effects gravty regresson and the supply shfters are estmated from a regresson of log ncome on geographc and nsttutonal controls. The scatter plots are plots of the resduals after controllng for the drect effect of the geographc, hstorcal, and nsttutonal observables. 67

28 Fgure 5: The network effect of a U.S.-Chna trade war: Degree 0 Notes: Ths fgure depcts the degree 0 effect of an ncrease n the blateral trade frctons between the U.S. and Chna a trade war ) n all countres. The degree 0 effect s the drect mpact of the trade war on the U.S. and Chna, holdng constant the prce and output n all other countres. Note that output prces, output, and the prce ndex effects are dentfed only to scale, whereas the level of ncome and real output prces are known see the dscusson n Secton 2). 68

29 Fgure 6: The network effect of a U.S.-Chna trade war: Degree 1 Notes: Ths fgure depcts the degree 1 effect of an ncrease n the blateral trade frctons between the U.S. and Chna a trade war ) n all countres. The degree 1 effect s the mpact of the degree 0 shock on all countres through the trade network, holdng constant the prces and output of ther tradng partners. Note that output prces, output, and the prce ndex effects are dentfed only to scale, whereas the level of ncome and real output prces are known see the dscusson n Secton 2). 69

30 Fgure 7: The network effect of a U.S.-Chna trade war: Degree 2 Notes: Ths fgure depcts the degree 2 effect of an ncrease n the blateral trade frctons between the U.S. and Chna a trade war ) n all countres. The degree 2 effect s the mpact of the degree 1 shock on all countres through the trade network, holdng constant the prces and output of ther tradng partners. Note that output prces, output, and the prce ndex effects are dentfed only to scale, whereas the level of ncome and real output prces are known see the dscusson n Secton 2). 70

31 Fgure 8: The network effect of a U.S.-Chna trade war: Degrees >2 Notes: Ths fgure depcts the cumulatve effect of all degrees greater than two of an ncrease n the blateral trade frctons between the U.S. and Chna a trade war ) n all countres. A degree k effect s the mpact of a degree k 1 shock on all countres through the trade network, holdng constant the prces and output of ther tradng partners. Note that output prces, output, and the prce ndex effects are dentfed only to scale, whereas the level of ncome and real output prces are known see the dscusson n Secton 2). 71

32 Fgure 9: The network effect of a U.S.-Chna trade war: Total effect Notes: Ths fgure depcts the total effect of an ncrease n the blateral trade frctons between the U.S. and Chna a trade war ) n all countres. Ths s the nfnte sum of all degree k effects. Note that output prces, output, and the prce ndex effects are dentfed only to scale, whereas the level of ncome and real output prces are known see the dscusson n Secton 2). 72

33 Fgure 10: Local versus global effects of a U.S.-Chna trade war Notes: Ths fgure depcts the correlaton of the local nfntesmal) elastctes and the global 50% ncrease) mpacts of a trade war on the real output prce n each country. 73

34 Fgure 11: The effect of a U.S.-Chna trade war on real output prces n the U.S. and Chna: Robustness US Supply elastcty Supply elastcty Demand elastcty Chna Demand elastcty Notes: Ths fgure depcts the elastcty of real output prces to an ncrease blateral trade frctons between the U.S. and Chna a trade war ) for many constellatons of demand and supply elastctes and ψ, respectvely. The star ndcates the estmated supply and demand elastcty constellaton, and the red box outlnes the 95% confdence nterval of the two parameters. 74

35 Fgure 12: Excess non-monotonc demand functon for 1, Z 1 p 2 )

Online Appendix: Reciprocity with Many Goods

Online Appendix: Reciprocity with Many Goods T D T A : O A Kyle Bagwell Stanford Unversty and NBER Robert W. Stager Dartmouth College and NBER March 2016 Abstract Ths onlne Appendx extends to a many-good settng the man features of recprocty emphaszed

More information

More metrics on cartesian products

More metrics on cartesian products More metrcs on cartesan products If (X, d ) are metrc spaces for 1 n, then n Secton II4 of the lecture notes we defned three metrcs on X whose underlyng topologes are the product topology The purpose of

More information

Welfare Properties of General Equilibrium. What can be said about optimality properties of resource allocation implied by general equilibrium?

Welfare Properties of General Equilibrium. What can be said about optimality properties of resource allocation implied by general equilibrium? APPLIED WELFARE ECONOMICS AND POLICY ANALYSIS Welfare Propertes of General Equlbrum What can be sad about optmalty propertes of resource allocaton mpled by general equlbrum? Any crteron used to compare

More information

,, MRTS is the marginal rate of technical substitution

,, MRTS is the marginal rate of technical substitution Mscellaneous Notes on roducton Economcs ompled by eter F Orazem September 9, 00 I Implcatons of conve soquants Two nput case, along an soquant 0 along an soquant Slope of the soquant,, MRTS s the margnal

More information

Lectures - Week 4 Matrix norms, Conditioning, Vector Spaces, Linear Independence, Spanning sets and Basis, Null space and Range of a Matrix

Lectures - Week 4 Matrix norms, Conditioning, Vector Spaces, Linear Independence, Spanning sets and Basis, Null space and Range of a Matrix Lectures - Week 4 Matrx norms, Condtonng, Vector Spaces, Lnear Independence, Spannng sets and Bass, Null space and Range of a Matrx Matrx Norms Now we turn to assocatng a number to each matrx. We could

More information

A NOTE ON CES FUNCTIONS Drago Bergholt, BI Norwegian Business School 2011

A NOTE ON CES FUNCTIONS Drago Bergholt, BI Norwegian Business School 2011 A NOTE ON CES FUNCTIONS Drago Bergholt, BI Norwegan Busness School 2011 Functons featurng constant elastcty of substtuton CES are wdely used n appled economcs and fnance. In ths note, I do two thngs. Frst,

More information

Difference Equations

Difference Equations Dfference Equatons c Jan Vrbk 1 Bascs Suppose a sequence of numbers, say a 0,a 1,a,a 3,... s defned by a certan general relatonshp between, say, three consecutve values of the sequence, e.g. a + +3a +1

More information

Problem Set 3. 1 Offshoring as a Rybzcynski Effect. Economics 245 Fall 2011 International Trade

Problem Set 3. 1 Offshoring as a Rybzcynski Effect. Economics 245 Fall 2011 International Trade Due: Thu, December 1, 2011 Instructor: Marc-Andreas Muendler E-mal: muendler@ucsd.edu Economcs 245 Fall 2011 Internatonal Trade Problem Set 3 November 15, 2011 1 Offshorng as a Rybzcynsk Effect There are

More information

APPENDIX A Some Linear Algebra

APPENDIX A Some Linear Algebra APPENDIX A Some Lnear Algebra The collecton of m, n matrces A.1 Matrces a 1,1,..., a 1,n A = a m,1,..., a m,n wth real elements a,j s denoted by R m,n. If n = 1 then A s called a column vector. Smlarly,

More information

princeton univ. F 17 cos 521: Advanced Algorithm Design Lecture 7: LP Duality Lecturer: Matt Weinberg

princeton univ. F 17 cos 521: Advanced Algorithm Design Lecture 7: LP Duality Lecturer: Matt Weinberg prnceton unv. F 17 cos 521: Advanced Algorthm Desgn Lecture 7: LP Dualty Lecturer: Matt Wenberg Scrbe: LP Dualty s an extremely useful tool for analyzng structural propertes of lnear programs. Whle there

More information

Economics 101. Lecture 4 - Equilibrium and Efficiency

Economics 101. Lecture 4 - Equilibrium and Efficiency Economcs 0 Lecture 4 - Equlbrum and Effcency Intro As dscussed n the prevous lecture, we wll now move from an envronment where we looed at consumers mang decsons n solaton to analyzng economes full of

More information

Affine transformations and convexity

Affine transformations and convexity Affne transformatons and convexty The purpose of ths document s to prove some basc propertes of affne transformatons nvolvng convex sets. Here are a few onlne references for background nformaton: http://math.ucr.edu/

More information

Mixed Taxation and Production Efficiency

Mixed Taxation and Production Efficiency Floran Scheuer 2/23/2016 Mxed Taxaton and Producton Effcency 1 Overvew 1. Unform commodty taxaton under non-lnear ncome taxaton Atknson-Stgltz (JPubE 1976) Theorem Applcaton to captal taxaton 2. Unform

More information

Inner Product. Euclidean Space. Orthonormal Basis. Orthogonal

Inner Product. Euclidean Space. Orthonormal Basis. Orthogonal Inner Product Defnton 1 () A Eucldean space s a fnte-dmensonal vector space over the reals R, wth an nner product,. Defnton 2 (Inner Product) An nner product, on a real vector space X s a symmetrc, blnear,

More information

e - c o m p a n i o n

e - c o m p a n i o n OPERATIONS RESEARCH http://dxdoorg/0287/opre007ec e - c o m p a n o n ONLY AVAILABLE IN ELECTRONIC FORM 202 INFORMS Electronc Companon Generalzed Quantty Competton for Multple Products and Loss of Effcency

More information

ANSWERS. Problem 1. and the moment generating function (mgf) by. defined for any real t. Use this to show that E( U) var( U)

ANSWERS. Problem 1. and the moment generating function (mgf) by. defined for any real t. Use this to show that E( U) var( U) Econ 413 Exam 13 H ANSWERS Settet er nndelt 9 deloppgaver, A,B,C, som alle anbefales å telle lkt for å gøre det ltt lettere å stå. Svar er gtt . Unfortunately, there s a prntng error n the hnt of

More information

3.1 Expectation of Functions of Several Random Variables. )' be a k-dimensional discrete or continuous random vector, with joint PMF p (, E X E X1 E X

3.1 Expectation of Functions of Several Random Variables. )' be a k-dimensional discrete or continuous random vector, with joint PMF p (, E X E X1 E X Statstcs 1: Probablty Theory II 37 3 EPECTATION OF SEVERAL RANDOM VARIABLES As n Probablty Theory I, the nterest n most stuatons les not on the actual dstrbuton of a random vector, but rather on a number

More information

Appendix B. Criterion of Riemann-Stieltjes Integrability

Appendix B. Criterion of Riemann-Stieltjes Integrability Appendx B. Crteron of Remann-Steltes Integrablty Ths note s complementary to [R, Ch. 6] and [T, Sec. 3.5]. The man result of ths note s Theorem B.3, whch provdes the necessary and suffcent condtons for

More information

Chapter 5. Solution of System of Linear Equations. Module No. 6. Solution of Inconsistent and Ill Conditioned Systems

Chapter 5. Solution of System of Linear Equations. Module No. 6. Solution of Inconsistent and Ill Conditioned Systems Numercal Analyss by Dr. Anta Pal Assstant Professor Department of Mathematcs Natonal Insttute of Technology Durgapur Durgapur-713209 emal: anta.bue@gmal.com 1 . Chapter 5 Soluton of System of Lnear Equatons

More information

(1 ) (1 ) 0 (1 ) (1 ) 0

(1 ) (1 ) 0 (1 ) (1 ) 0 Appendx A Appendx A contans proofs for resubmsson "Contractng Informaton Securty n the Presence of Double oral Hazard" Proof of Lemma 1: Assume that, to the contrary, BS efforts are achevable under a blateral

More information

Appendix for Causal Interaction in Factorial Experiments: Application to Conjoint Analysis

Appendix for Causal Interaction in Factorial Experiments: Application to Conjoint Analysis A Appendx for Causal Interacton n Factoral Experments: Applcaton to Conjont Analyss Mathematcal Appendx: Proofs of Theorems A. Lemmas Below, we descrbe all the lemmas, whch are used to prove the man theorems

More information

The Multiple Classical Linear Regression Model (CLRM): Specification and Assumptions. 1. Introduction

The Multiple Classical Linear Regression Model (CLRM): Specification and Assumptions. 1. Introduction ECONOMICS 5* -- NOTE (Summary) ECON 5* -- NOTE The Multple Classcal Lnear Regresson Model (CLRM): Specfcaton and Assumptons. Introducton CLRM stands for the Classcal Lnear Regresson Model. The CLRM s also

More information

k t+1 + c t A t k t, t=0

k t+1 + c t A t k t, t=0 Macro II (UC3M, MA/PhD Econ) Professor: Matthas Kredler Fnal Exam 6 May 208 You have 50 mnutes to complete the exam There are 80 ponts n total The exam has 4 pages If somethng n the queston s unclear,

More information

MMA and GCMMA two methods for nonlinear optimization

MMA and GCMMA two methods for nonlinear optimization MMA and GCMMA two methods for nonlnear optmzaton Krster Svanberg Optmzaton and Systems Theory, KTH, Stockholm, Sweden. krlle@math.kth.se Ths note descrbes the algorthms used n the author s 2007 mplementatons

More information

a b a In case b 0, a being divisible by b is the same as to say that

a b a In case b 0, a being divisible by b is the same as to say that Secton 6.2 Dvsblty among the ntegers An nteger a ε s dvsble by b ε f there s an nteger c ε such that a = bc. Note that s dvsble by any nteger b, snce = b. On the other hand, a s dvsble by only f a = :

More information

First day August 1, Problems and Solutions

First day August 1, Problems and Solutions FOURTH INTERNATIONAL COMPETITION FOR UNIVERSITY STUDENTS IN MATHEMATICS July 30 August 4, 997, Plovdv, BULGARIA Frst day August, 997 Problems and Solutons Problem. Let {ε n } n= be a sequence of postve

More information

Norm Bounds for a Transformed Activity Level. Vector in Sraffian Systems: A Dual Exercise

Norm Bounds for a Transformed Activity Level. Vector in Sraffian Systems: A Dual Exercise ppled Mathematcal Scences, Vol. 4, 200, no. 60, 2955-296 Norm Bounds for a ransformed ctvty Level Vector n Sraffan Systems: Dual Exercse Nkolaos Rodousaks Department of Publc dmnstraton, Panteon Unversty

More information

Foundations of Arithmetic

Foundations of Arithmetic Foundatons of Arthmetc Notaton We shall denote the sum and product of numbers n the usual notaton as a 2 + a 2 + a 3 + + a = a, a 1 a 2 a 3 a = a The notaton a b means a dvdes b,.e. ac = b where c s an

More information

BOUNDEDNESS OF THE RIESZ TRANSFORM WITH MATRIX A 2 WEIGHTS

BOUNDEDNESS OF THE RIESZ TRANSFORM WITH MATRIX A 2 WEIGHTS BOUNDEDNESS OF THE IESZ TANSFOM WITH MATIX A WEIGHTS Introducton Let L = L ( n, be the functon space wth norm (ˆ f L = f(x C dx d < For a d d matrx valued functon W : wth W (x postve sem-defnte for all

More information

Econ107 Applied Econometrics Topic 3: Classical Model (Studenmund, Chapter 4)

Econ107 Applied Econometrics Topic 3: Classical Model (Studenmund, Chapter 4) I. Classcal Assumptons Econ7 Appled Econometrcs Topc 3: Classcal Model (Studenmund, Chapter 4) We have defned OLS and studed some algebrac propertes of OLS. In ths topc we wll study statstcal propertes

More information

ELASTIC WAVE PROPAGATION IN A CONTINUOUS MEDIUM

ELASTIC WAVE PROPAGATION IN A CONTINUOUS MEDIUM ELASTIC WAVE PROPAGATION IN A CONTINUOUS MEDIUM An elastc wave s a deformaton of the body that travels throughout the body n all drectons. We can examne the deformaton over a perod of tme by fxng our look

More information

Perfect Competition and the Nash Bargaining Solution

Perfect Competition and the Nash Bargaining Solution Perfect Competton and the Nash Barganng Soluton Renhard John Department of Economcs Unversty of Bonn Adenauerallee 24-42 53113 Bonn, Germany emal: rohn@un-bonn.de May 2005 Abstract For a lnear exchange

More information

Formulas for the Determinant

Formulas for the Determinant page 224 224 CHAPTER 3 Determnants e t te t e 2t 38 A = e t 2te t e 2t e t te t 2e 2t 39 If 123 A = 345, 456 compute the matrx product A adj(a) What can you conclude about det(a)? For Problems 40 43, use

More information

n α j x j = 0 j=1 has a nontrivial solution. Here A is the n k matrix whose jth column is the vector for all t j=0

n α j x j = 0 j=1 has a nontrivial solution. Here A is the n k matrix whose jth column is the vector for all t j=0 MODULE 2 Topcs: Lnear ndependence, bass and dmenson We have seen that f n a set of vectors one vector s a lnear combnaton of the remanng vectors n the set then the span of the set s unchanged f that vector

More information

1. relation between exp. function and IUF

1. relation between exp. function and IUF Dualty Dualty n consumer theory II. relaton between exp. functon and IUF - straghtforward: have m( p, u mn'd value of expendture requred to attan a gven level of utlty, gven a prce vector; u ( p, M max'd

More information

Salmon: Lectures on partial differential equations. Consider the general linear, second-order PDE in the form. ,x 2

Salmon: Lectures on partial differential equations. Consider the general linear, second-order PDE in the form. ,x 2 Salmon: Lectures on partal dfferental equatons 5. Classfcaton of second-order equatons There are general methods for classfyng hgher-order partal dfferental equatons. One s very general (applyng even to

More information

How Strong Are Weak Patents? Joseph Farrell and Carl Shapiro. Supplementary Material Licensing Probabilistic Patents to Cournot Oligopolists *

How Strong Are Weak Patents? Joseph Farrell and Carl Shapiro. Supplementary Material Licensing Probabilistic Patents to Cournot Oligopolists * How Strong Are Weak Patents? Joseph Farrell and Carl Shapro Supplementary Materal Lcensng Probablstc Patents to Cournot Olgopolsts * September 007 We study here the specal case n whch downstream competton

More information

Lecture 10 Optimal Growth Endogenous Growth. Noah Williams

Lecture 10 Optimal Growth Endogenous Growth. Noah Williams Lecture 10 Optimal Growth Endogenous Growth Noah Williams University of Wisconsin - Madison Economics 702 Spring 2018 Optimal Growth Path Recall we assume exogenous growth in population and productivity:

More information

Exercise Solutions to Real Analysis

Exercise Solutions to Real Analysis xercse Solutons to Real Analyss Note: References refer to H. L. Royden, Real Analyss xersze 1. Gven any set A any ɛ > 0, there s an open set O such that A O m O m A + ɛ. Soluton 1. If m A =, then there

More information

Assortment Optimization under MNL

Assortment Optimization under MNL Assortment Optmzaton under MNL Haotan Song Aprl 30, 2017 1 Introducton The assortment optmzaton problem ams to fnd the revenue-maxmzng assortment of products to offer when the prces of products are fxed.

More information

Complete subgraphs in multipartite graphs

Complete subgraphs in multipartite graphs Complete subgraphs n multpartte graphs FLORIAN PFENDER Unverstät Rostock, Insttut für Mathematk D-18057 Rostock, Germany Floran.Pfender@un-rostock.de Abstract Turán s Theorem states that every graph G

More information

Lecture 12: Discrete Laplacian

Lecture 12: Discrete Laplacian Lecture 12: Dscrete Laplacan Scrbe: Tanye Lu Our goal s to come up wth a dscrete verson of Laplacan operator for trangulated surfaces, so that we can use t n practce to solve related problems We are mostly

More information

Linear, affine, and convex sets and hulls In the sequel, unless otherwise specified, X will denote a real vector space.

Linear, affine, and convex sets and hulls In the sequel, unless otherwise specified, X will denote a real vector space. Lnear, affne, and convex sets and hulls In the sequel, unless otherwse specfed, X wll denote a real vector space. Lnes and segments. Gven two ponts x, y X, we defne xy = {x + t(y x) : t R} = {(1 t)x +

More information

COS 521: Advanced Algorithms Game Theory and Linear Programming

COS 521: Advanced Algorithms Game Theory and Linear Programming COS 521: Advanced Algorthms Game Theory and Lnear Programmng Moses Charkar February 27, 2013 In these notes, we ntroduce some basc concepts n game theory and lnear programmng (LP). We show a connecton

More information

Solutions to exam in SF1811 Optimization, Jan 14, 2015

Solutions to exam in SF1811 Optimization, Jan 14, 2015 Solutons to exam n SF8 Optmzaton, Jan 4, 25 3 3 O------O -4 \ / \ / The network: \/ where all lnks go from left to rght. /\ / \ / \ 6 O------O -5 2 4.(a) Let x = ( x 3, x 4, x 23, x 24 ) T, where the varable

More information

Spectral Graph Theory and its Applications September 16, Lecture 5

Spectral Graph Theory and its Applications September 16, Lecture 5 Spectral Graph Theory and ts Applcatons September 16, 2004 Lecturer: Danel A. Spelman Lecture 5 5.1 Introducton In ths lecture, we wll prove the followng theorem: Theorem 5.1.1. Let G be a planar graph

More information

Perron Vectors of an Irreducible Nonnegative Interval Matrix

Perron Vectors of an Irreducible Nonnegative Interval Matrix Perron Vectors of an Irreducble Nonnegatve Interval Matrx Jr Rohn August 4 2005 Abstract As s well known an rreducble nonnegatve matrx possesses a unquely determned Perron vector. As the man result of

More information

The Geometry of Logit and Probit

The Geometry of Logit and Probit The Geometry of Logt and Probt Ths short note s meant as a supplement to Chapters and 3 of Spatal Models of Parlamentary Votng and the notaton and reference to fgures n the text below s to those two chapters.

More information

Lecture Notes, January 11, 2010

Lecture Notes, January 11, 2010 Economcs 200B UCSD Wnter 2010 Lecture otes, January 11, 2010 Partal equlbrum comparatve statcs Partal equlbrum: Market for one good only wth supply and demand as a functon of prce. Prce s defned as the

More information

Online Appendix for Trade and Insecure Resources

Online Appendix for Trade and Insecure Resources B Onlne ppendx for Trade and Insecure Resources Proof of Lemma.: Followng Jones 965, we denote the shares of factor h = K, L n the cost of producng good j =, 2 by θ hj : θ Kj = r a Kj /c j and θ Lj = w

More information

Introductory Cardinality Theory Alan Kaylor Cline

Introductory Cardinality Theory Alan Kaylor Cline Introductory Cardnalty Theory lan Kaylor Clne lthough by name the theory of set cardnalty may seem to be an offshoot of combnatorcs, the central nterest s actually nfnte sets. Combnatorcs deals wth fnte

More information

Let p z be the price of z and p 1 and p 2 be the prices of the goods making up y. In general there is no problem in grouping goods.

Let p z be the price of z and p 1 and p 2 be the prices of the goods making up y. In general there is no problem in grouping goods. Economcs 90 Prce Theory ON THE QUESTION OF SEPARABILITY What we would lke to be able to do s estmate demand curves by segmentng consumers purchases nto groups. In one applcaton, we aggregate purchases

More information

Errors for Linear Systems

Errors for Linear Systems Errors for Lnear Systems When we solve a lnear system Ax b we often do not know A and b exactly, but have only approxmatons  and ˆb avalable. Then the best thng we can do s to solve ˆx ˆb exactly whch

More information

The Order Relation and Trace Inequalities for. Hermitian Operators

The Order Relation and Trace Inequalities for. Hermitian Operators Internatonal Mathematcal Forum, Vol 3, 08, no, 507-57 HIKARI Ltd, wwwm-hkarcom https://doorg/0988/mf088055 The Order Relaton and Trace Inequaltes for Hermtan Operators Y Huang School of Informaton Scence

More information

MATH 241B FUNCTIONAL ANALYSIS - NOTES EXAMPLES OF C ALGEBRAS

MATH 241B FUNCTIONAL ANALYSIS - NOTES EXAMPLES OF C ALGEBRAS MATH 241B FUNCTIONAL ANALYSIS - NOTES EXAMPLES OF C ALGEBRAS These are nformal notes whch cover some of the materal whch s not n the course book. The man purpose s to gve a number of nontrval examples

More information

LINEAR REGRESSION ANALYSIS. MODULE IX Lecture Multicollinearity

LINEAR REGRESSION ANALYSIS. MODULE IX Lecture Multicollinearity LINEAR REGRESSION ANALYSIS MODULE IX Lecture - 30 Multcollnearty Dr. Shalabh Department of Mathematcs and Statstcs Indan Insttute of Technology Kanpur 2 Remedes for multcollnearty Varous technques have

More information

Supplementary Notes for Chapter 9 Mixture Thermodynamics

Supplementary Notes for Chapter 9 Mixture Thermodynamics Supplementary Notes for Chapter 9 Mxture Thermodynamcs Key ponts Nne major topcs of Chapter 9 are revewed below: 1. Notaton and operatonal equatons for mxtures 2. PVTN EOSs for mxtures 3. General effects

More information

Limited Dependent Variables

Limited Dependent Variables Lmted Dependent Varables. What f the left-hand sde varable s not a contnuous thng spread from mnus nfnty to plus nfnty? That s, gven a model = f (, β, ε, where a. s bounded below at zero, such as wages

More information

DIFFERENTIAL FORMS BRIAN OSSERMAN

DIFFERENTIAL FORMS BRIAN OSSERMAN DIFFERENTIAL FORMS BRIAN OSSERMAN Dfferentals are an mportant topc n algebrac geometry, allowng the use of some classcal geometrc arguments n the context of varetes over any feld. We wll use them to defne

More information

Linear Approximation with Regularization and Moving Least Squares

Linear Approximation with Regularization and Moving Least Squares Lnear Approxmaton wth Regularzaton and Movng Least Squares Igor Grešovn May 007 Revson 4.6 (Revson : March 004). 5 4 3 0.5 3 3.5 4 Contents: Lnear Fttng...4. Weghted Least Squares n Functon Approxmaton...

More information

On the symmetric character of the thermal conductivity tensor

On the symmetric character of the thermal conductivity tensor On the symmetrc character of the thermal conductvty tensor Al R. Hadjesfandar Department of Mechancal and Aerospace Engneerng Unversty at Buffalo, State Unversty of New York Buffalo, NY 146 USA ah@buffalo.edu

More information

C/CS/Phy191 Problem Set 3 Solutions Out: Oct 1, 2008., where ( 00. ), so the overall state of the system is ) ( ( ( ( 00 ± 11 ), Φ ± = 1

C/CS/Phy191 Problem Set 3 Solutions Out: Oct 1, 2008., where ( 00. ), so the overall state of the system is ) ( ( ( ( 00 ± 11 ), Φ ± = 1 C/CS/Phy9 Problem Set 3 Solutons Out: Oct, 8 Suppose you have two qubts n some arbtrary entangled state ψ You apply the teleportaton protocol to each of the qubts separately What s the resultng state obtaned

More information

FINITELY-GENERATED MODULES OVER A PRINCIPAL IDEAL DOMAIN

FINITELY-GENERATED MODULES OVER A PRINCIPAL IDEAL DOMAIN FINITELY-GENERTED MODULES OVER PRINCIPL IDEL DOMIN EMMNUEL KOWLSKI Throughout ths note, s a prncpal deal doman. We recall the classfcaton theorem: Theorem 1. Let M be a fntely-generated -module. (1) There

More information

Endogenous timing in a mixed oligopoly consisting of a single public firm and foreign competitors. Abstract

Endogenous timing in a mixed oligopoly consisting of a single public firm and foreign competitors. Abstract Endogenous tmng n a mxed olgopoly consstng o a sngle publc rm and oregn compettors Yuanzhu Lu Chna Economcs and Management Academy, Central Unversty o Fnance and Economcs Abstract We nvestgate endogenous

More information

SL n (F ) Equals its Own Derived Group

SL n (F ) Equals its Own Derived Group Internatonal Journal of Algebra, Vol. 2, 2008, no. 12, 585-594 SL n (F ) Equals ts Own Derved Group Jorge Macel BMCC-The Cty Unversty of New York, CUNY 199 Chambers street, New York, NY 10007, USA macel@cms.nyu.edu

More information

Stanford University CS359G: Graph Partitioning and Expanders Handout 4 Luca Trevisan January 13, 2011

Stanford University CS359G: Graph Partitioning and Expanders Handout 4 Luca Trevisan January 13, 2011 Stanford Unversty CS359G: Graph Parttonng and Expanders Handout 4 Luca Trevsan January 3, 0 Lecture 4 In whch we prove the dffcult drecton of Cheeger s nequalty. As n the past lectures, consder an undrected

More information

10-801: Advanced Optimization and Randomized Methods Lecture 2: Convex functions (Jan 15, 2014)

10-801: Advanced Optimization and Randomized Methods Lecture 2: Convex functions (Jan 15, 2014) 0-80: Advanced Optmzaton and Randomzed Methods Lecture : Convex functons (Jan 5, 04) Lecturer: Suvrt Sra Addr: Carnege Mellon Unversty, Sprng 04 Scrbes: Avnava Dubey, Ahmed Hefny Dsclamer: These notes

More information

CSCE 790S Background Results

CSCE 790S Background Results CSCE 790S Background Results Stephen A. Fenner September 8, 011 Abstract These results are background to the course CSCE 790S/CSCE 790B, Quantum Computaton and Informaton (Sprng 007 and Fall 011). Each

More information

Introduction to Vapor/Liquid Equilibrium, part 2. Raoult s Law:

Introduction to Vapor/Liquid Equilibrium, part 2. Raoult s Law: CE304, Sprng 2004 Lecture 4 Introducton to Vapor/Lqud Equlbrum, part 2 Raoult s Law: The smplest model that allows us do VLE calculatons s obtaned when we assume that the vapor phase s an deal gas, and

More information

Linear Algebra and its Applications

Linear Algebra and its Applications Lnear Algebra and ts Applcatons 4 (00) 5 56 Contents lsts avalable at ScenceDrect Lnear Algebra and ts Applcatons journal homepage: wwwelsevercom/locate/laa Notes on Hlbert and Cauchy matrces Mroslav Fedler

More information

Mathematical Preparations

Mathematical Preparations 1 Introducton Mathematcal Preparatons The theory of relatvty was developed to explan experments whch studed the propagaton of electromagnetc radaton n movng coordnate systems. Wthn expermental error the

More information

CSci 6974 and ECSE 6966 Math. Tech. for Vision, Graphics and Robotics Lecture 21, April 17, 2006 Estimating A Plane Homography

CSci 6974 and ECSE 6966 Math. Tech. for Vision, Graphics and Robotics Lecture 21, April 17, 2006 Estimating A Plane Homography CSc 6974 and ECSE 6966 Math. Tech. for Vson, Graphcs and Robotcs Lecture 21, Aprl 17, 2006 Estmatng A Plane Homography Overvew We contnue wth a dscusson of the major ssues, usng estmaton of plane projectve

More information

Supplement: Proofs and Technical Details for The Solution Path of the Generalized Lasso

Supplement: Proofs and Technical Details for The Solution Path of the Generalized Lasso Supplement: Proofs and Techncal Detals for The Soluton Path of the Generalzed Lasso Ryan J. Tbshran Jonathan Taylor In ths document we gve supplementary detals to the paper The Soluton Path of the Generalzed

More information

COMPLEX NUMBERS AND QUADRATIC EQUATIONS

COMPLEX NUMBERS AND QUADRATIC EQUATIONS COMPLEX NUMBERS AND QUADRATIC EQUATIONS INTRODUCTION We know that x 0 for all x R e the square of a real number (whether postve, negatve or ero) s non-negatve Hence the equatons x, x, x + 7 0 etc are not

More information

Open Systems: Chemical Potential and Partial Molar Quantities Chemical Potential

Open Systems: Chemical Potential and Partial Molar Quantities Chemical Potential Open Systems: Chemcal Potental and Partal Molar Quanttes Chemcal Potental For closed systems, we have derved the followng relatonshps: du = TdS pdv dh = TdS + Vdp da = SdT pdv dg = VdP SdT For open systems,

More information

THE CHINESE REMAINDER THEOREM. We should thank the Chinese for their wonderful remainder theorem. Glenn Stevens

THE CHINESE REMAINDER THEOREM. We should thank the Chinese for their wonderful remainder theorem. Glenn Stevens THE CHINESE REMAINDER THEOREM KEITH CONRAD We should thank the Chnese for ther wonderful remander theorem. Glenn Stevens 1. Introducton The Chnese remander theorem says we can unquely solve any par of

More information

12 MATH 101A: ALGEBRA I, PART C: MULTILINEAR ALGEBRA. 4. Tensor product

12 MATH 101A: ALGEBRA I, PART C: MULTILINEAR ALGEBRA. 4. Tensor product 12 MATH 101A: ALGEBRA I, PART C: MULTILINEAR ALGEBRA Here s an outlne of what I dd: (1) categorcal defnton (2) constructon (3) lst of basc propertes (4) dstrbutve property (5) rght exactness (6) localzaton

More information

Economics 130. Lecture 4 Simple Linear Regression Continued

Economics 130. Lecture 4 Simple Linear Regression Continued Economcs 130 Lecture 4 Contnued Readngs for Week 4 Text, Chapter and 3. We contnue wth addressng our second ssue + add n how we evaluate these relatonshps: Where do we get data to do ths analyss? How do

More information

Structure and Drive Paul A. Jensen Copyright July 20, 2003

Structure and Drive Paul A. Jensen Copyright July 20, 2003 Structure and Drve Paul A. Jensen Copyrght July 20, 2003 A system s made up of several operatons wth flow passng between them. The structure of the system descrbes the flow paths from nputs to outputs.

More information

Problem Set 9 Solutions

Problem Set 9 Solutions Desgn and Analyss of Algorthms May 4, 2015 Massachusetts Insttute of Technology 6.046J/18.410J Profs. Erk Demane, Srn Devadas, and Nancy Lynch Problem Set 9 Solutons Problem Set 9 Solutons Ths problem

More information

The Feynman path integral

The Feynman path integral The Feynman path ntegral Aprl 3, 205 Hesenberg and Schrödnger pctures The Schrödnger wave functon places the tme dependence of a physcal system n the state, ψ, t, where the state s a vector n Hlbert space

More information

f(x,y) = (4(x 2 4)x,2y) = 0 H(x,y) =

f(x,y) = (4(x 2 4)x,2y) = 0 H(x,y) = Problem Set 3: Unconstraned mzaton n R N. () Fnd all crtcal ponts of f(x,y) (x 4) +y and show whch are ma and whch are mnma. () Fnd all crtcal ponts of f(x,y) (y x ) x and show whch are ma and whch are

More information

find (x): given element x, return the canonical element of the set containing x;

find (x): given element x, return the canonical element of the set containing x; COS 43 Sprng, 009 Dsjont Set Unon Problem: Mantan a collecton of dsjont sets. Two operatons: fnd the set contanng a gven element; unte two sets nto one (destructvely). Approach: Canoncal element method:

More information

Yong Joon Ryang. 1. Introduction Consider the multicommodity transportation problem with convex quadratic cost function. 1 2 (x x0 ) T Q(x x 0 )

Yong Joon Ryang. 1. Introduction Consider the multicommodity transportation problem with convex quadratic cost function. 1 2 (x x0 ) T Q(x x 0 ) Kangweon-Kyungk Math. Jour. 4 1996), No. 1, pp. 7 16 AN ITERATIVE ROW-ACTION METHOD FOR MULTICOMMODITY TRANSPORTATION PROBLEMS Yong Joon Ryang Abstract. The optmzaton problems wth quadratc constrants often

More information

REAL ANALYSIS I HOMEWORK 1

REAL ANALYSIS I HOMEWORK 1 REAL ANALYSIS I HOMEWORK CİHAN BAHRAN The questons are from Tao s text. Exercse 0.0.. If (x α ) α A s a collecton of numbers x α [0, + ] such that x α

More information

Inferring Latent Preferences from Network Data

Inferring Latent Preferences from Network Data Inferring Latent Preferences from Network John S. Ahlquist 1 Arturas 2 1 UC San Diego GPS 2 NYU 14 November 2015 very early stages Methodological extend latent space models (Hoff et al 2002) to partial

More information

PHYS 705: Classical Mechanics. Calculus of Variations II

PHYS 705: Classical Mechanics. Calculus of Variations II 1 PHYS 705: Classcal Mechancs Calculus of Varatons II 2 Calculus of Varatons: Generalzaton (no constrant yet) Suppose now that F depends on several dependent varables : We need to fnd such that has a statonary

More information

U.C. Berkeley CS294: Spectral Methods and Expanders Handout 8 Luca Trevisan February 17, 2016

U.C. Berkeley CS294: Spectral Methods and Expanders Handout 8 Luca Trevisan February 17, 2016 U.C. Berkeley CS94: Spectral Methods and Expanders Handout 8 Luca Trevsan February 7, 06 Lecture 8: Spectral Algorthms Wrap-up In whch we talk about even more generalzatons of Cheeger s nequaltes, and

More information

Midterm Examination. Regression and Forecasting Models

Midterm Examination. Regression and Forecasting Models IOMS Department Regresson and Forecastng Models Professor Wllam Greene Phone: 22.998.0876 Offce: KMC 7-90 Home page: people.stern.nyu.edu/wgreene Emal: wgreene@stern.nyu.edu Course web page: people.stern.nyu.edu/wgreene/regresson/outlne.htm

More information

Week 2. This week, we covered operations on sets and cardinality.

Week 2. This week, we covered operations on sets and cardinality. Week 2 Ths week, we covered operatons on sets and cardnalty. Defnton 0.1 (Correspondence). A correspondence between two sets A and B s a set S contaned n A B = {(a, b) a A, b B}. A correspondence from

More information

Comparison of Regression Lines

Comparison of Regression Lines STATGRAPHICS Rev. 9/13/2013 Comparson of Regresson Lnes Summary... 1 Data Input... 3 Analyss Summary... 4 Plot of Ftted Model... 6 Condtonal Sums of Squares... 6 Analyss Optons... 7 Forecasts... 8 Confdence

More information

= = = (a) Use the MATLAB command rref to solve the system. (b) Let A be the coefficient matrix and B be the right-hand side of the system.

= = = (a) Use the MATLAB command rref to solve the system. (b) Let A be the coefficient matrix and B be the right-hand side of the system. Chapter Matlab Exercses Chapter Matlab Exercses. Consder the lnear system of Example n Secton.. x x x y z y y z (a) Use the MATLAB command rref to solve the system. (b) Let A be the coeffcent matrx and

More information

( ) 2 ( ) ( ) Problem Set 4 Suggested Solutions. Problem 1

( ) 2 ( ) ( ) Problem Set 4 Suggested Solutions. Problem 1 Problem Set 4 Suggested Solutons Problem (A) The market demand functon s the soluton to the followng utlty-maxmzaton roblem (UMP): The Lagrangean: ( x, x, x ) = + max U x, x, x x x x st.. x + x + x y x,

More information

Online Appendix. t=1 (p t w)q t. Then the first order condition shows that

Online Appendix. t=1 (p t w)q t. Then the first order condition shows that Artcle forthcomng to ; manuscrpt no (Please, provde the manuscrpt number!) 1 Onlne Appendx Appendx E: Proofs Proof of Proposton 1 Frst we derve the equlbrum when the manufacturer does not vertcally ntegrate

More information

Canonical transformations

Canonical transformations Canoncal transformatons November 23, 2014 Recall that we have defned a symplectc transformaton to be any lnear transformaton M A B leavng the symplectc form nvarant, Ω AB M A CM B DΩ CD Coordnate transformatons,

More information

Graph Reconstruction by Permutations

Graph Reconstruction by Permutations Graph Reconstructon by Permutatons Perre Ille and Wllam Kocay* Insttut de Mathémathques de Lumny CNRS UMR 6206 163 avenue de Lumny, Case 907 13288 Marselle Cedex 9, France e-mal: lle@ml.unv-mrs.fr Computer

More information

Maximizing the number of nonnegative subsets

Maximizing the number of nonnegative subsets Maxmzng the number of nonnegatve subsets Noga Alon Hao Huang December 1, 213 Abstract Gven a set of n real numbers, f the sum of elements of every subset of sze larger than k s negatve, what s the maxmum

More information

Chapter 2 - The Simple Linear Regression Model S =0. e i is a random error. S β2 β. This is a minimization problem. Solution is a calculus exercise.

Chapter 2 - The Simple Linear Regression Model S =0. e i is a random error. S β2 β. This is a minimization problem. Solution is a calculus exercise. Chapter - The Smple Lnear Regresson Model The lnear regresson equaton s: where y + = β + β e for =,..., y and are observable varables e s a random error How can an estmaton rule be constructed for the

More information

Chapter 11: Simple Linear Regression and Correlation

Chapter 11: Simple Linear Regression and Correlation Chapter 11: Smple Lnear Regresson and Correlaton 11-1 Emprcal Models 11-2 Smple Lnear Regresson 11-3 Propertes of the Least Squares Estmators 11-4 Hypothess Test n Smple Lnear Regresson 11-4.1 Use of t-tests

More information

Solution Thermodynamics

Solution Thermodynamics Soluton hermodynamcs usng Wagner Notaton by Stanley. Howard Department of aterals and etallurgcal Engneerng South Dakota School of nes and echnology Rapd Cty, SD 57701 January 7, 001 Soluton hermodynamcs

More information