Optimal density of radial major roads in a two-dimensional monocentric city with endogenous residential distribution and housing prices

Size: px
Start display at page:

Download "Optimal density of radial major roads in a two-dimensional monocentric city with endogenous residential distribution and housing prices"

Transcription

1 Ttle Optmal densty of radal major roads n a two-dmensonal monocentrc cty wth endogenous resdental dstrbuton and housng prces Author(s) L, ZC; Chen, YJ; Wang, YD; Lam, WHK; Wong, SC Ctaton Regonal Scence and Urban Economcs, 2013, v. 43 n. 6, p Issued Date 2013 URL Rghts NOTICE: ths s the author s verson of a work that was accepted for publcaton n Regonal Scence and Urban Economcs. Changes resultng from the publshng process, such as peer revew, edtng, correctons, structural formattng, and other qualty control mechansms may not be reflected n ths document. Changes may have been made to ths work snce t was submtted for publcaton. A defntve verson was subsequently publshed n Regonal Scence and Urban Economcs, 2013, v. 43 n. 6, p DOI: /j.regscurbeco

2 Optmal densty of radal major roads n a two-dmensonal monocentrc cty wth endogenous resdental dstrbuton and housng prces Zh-Chun L a,*, Ya-Juan Chen a, Ya-Dong Wang a, Wllam H. K. Lam b,c, S. C. Wong d a School of Management, Huazhong Unversty of Scence and Technology, Wuhan , Chna b Department of Cvl and Structural Engneerng, The Hong Kong Polytechnc Unversty, Kowloon, Hong Kong, Chna c School of Traffc & Transportaton, Bejng Jaotong Unversty, Bejng , Chna d Department of Cvl Engneerng, The Unversty of Hong Kong, Pokfulam Road, Hong Kong, Chna Abstract Ths paper proposes an analytcal urban system equlbrum model for optmzng the densty of radal major roads n a two-dmensonal monocentrc cty. The proposed model nvolves four types of agents: local authortes, property developers, households and household workers (.e. commuters). The local authortes am to maxmze the total socal welfare of the urban system by determnng the optmal densty of radal major roads n the cty. The property developers seek to determne the ntensty of ther captal nvestment n the land market to maxmze the net proft generated from the housng supply. The households choose resdental locatons that maxmze ther utlty wthn a budget constrant, and the commuters choose the radal major roads that mnmze ther ndvdual costs of travel between home and workplace. A heurstc soluton procedure s developed to fnd the urban system equlbrum soluton. A system optmum model s also proposed to optmze the densty of radal major roads that maxmzes the socal welfare of the urban system. The proposed model can endogenously determne household resdental dstrbuton and land values across the cty, along wth the housng market structure n terms of housng prces and space. Numercal comparatve statc analyses of congeston prcng and road nfrastructure nvestment (addng a new radal major road) are carred out together wth evaluaton of the effects of the servce level of radal major roads, urban populaton sze, and household ncome level on the urban economy. Keywords: Two-dmensonal monocentrc cty; densty of radal major roads; urban system equlbrum; household resdental locaton choce; housng market; congeston prcng. * Correspondng author. Tel.: ; Fax: E-mal address: smzcl@gmal.com (Z.-C. L).

3 1. Introducton Many of the large modernzed ctes n Chna such as Bejng, Shangha and Wuhan have dramatcally ncreased n sze n recent years as a result of Chna s rapd urbanzaton and economc growth. Ths rapd urban expanson has led to a more decentralzed urban structure, longer average journey length, ncreased use of prvate cars, and hgher level of traffc congeston, partcularly wthn metropoltan areas. In response, local authortes have launched a number of transportaton nfrastructure mprovement projects to ncrease accessblty to the cty center and allevate urban traffc congeston, ncludng the constructon of radal major roads desgned to connect the cty s central busness dstrct (CBD) to ts suburban areas, as shown n Fg. 1. For example, the Wuhan muncpal government recently approved a proposal to buld a new radal major road wth a total length of 15 klometers to connect Gedan new town to Guanshan (Wuhan s CBD). Constructon for ths road project began n January 2012 and wll be completed at the end of The ntroducton of a new radal major road s expected to ncrease the capacty of a cty s transportaton system and mprove the accessblty of ts central area. Accordngly, the new radal major road can nfluence commuters road choces, whch affect the traffc flows and traffc congeston level on the major roads. However, the constructon of a new major road also nvolves a huge captal cost. The plannng and desgn of cty s radal major roads thus nvolve mportant welfare consderatons. Specfcally, an oversupply of major roads can lead to wastage of resources due to an neffcent use of road space. An undersupply of roads, n contrast, can result n traffc jams generated by a lack of suffcent road capacty to accommodate travel demand. Ths rases an nterestng queston: what s the optmal densty (or number) of radal major roads n terms of the total socal welfare (or surplus) of an urban system, partcularly when the cty boundary s expandng? The answer has long-term mplcatons for sustanable urban development, especally n rapdly expandng Chnese ctes such as Bejng, Shangha and Wuhan. To address ths mportant urban development ssue, advanced urban spatal models must be developed to help explan and evaluate the effects of dfferent denstes of radal major roads on the urban economy. In the classcal urban models that were developed by Alonso (1964), Mlls (1972) and Muth (1969), the urban transportaton network was assumed to be a 2

4 perfectly dvsble dense system consstng of an nfnte number of radal roads. These tradtonal urban models cannot be used to nvestgate the desgn ssue of the densty (or number) of urban radal major roads and evaluate the mpact of addng a new radal major road on the urban economy. One has thus to turn to a model that consders the urban structure as a sparse system of dscrete radal roads. In ths regard, Anas and Moses (1979) conducted a poneerng work. In ther work, t was assumed that commuters ether travel straght along dense surface streets to the cty center or travel along crcular dense surface streets to a radal road (.e. an expressway) and then travel along the radal road to get to the cty center (.e. a crcumferental-radal or rng-radal travel method). It was also assumed that the urban form was symmetrc (.e. the radal roads were evenly dstrbuted along the crcular cty) and there was no traffc congeston on the radal roads. The rng-radal travel method that they proposed s useful for modelng a dscrete-contnuous urban system (e.g., see Baum-Snow, 2007). However, the symmetry and congeston-free assumptons may cause a sgnfcant bas n the predcton capablty of the model, and thus restrct ts applcatons n practce. For example, congeston prcng ssues cannot be addressed under the congeston-free assumpton. D Este (1987) relaxed the assumptons of a symmetrc cty that s free of congeston, and proposed a trp assgnment model usng the rng-radal travel method of Anas and Moses (1979) to model commuters radal major road choces n a two-dmensonal monocentrc cty wth a small number of radal major roads. Wong (1994) reformulated D Este s trp assgnment model as a mathematcal programmng problem. These two studes assumed that the dstrbuton of resdental areas n the cty was exogenously gven and fxed. However, studes have shown that the mproved accessblty to road travel resultng from transportaton nfrastructure mprovements (e.g. ntroducng a new radal major road) can nduce changes n urban land-use patterns, land values and the housng market (n terms of housng prces and space) (e.g., see McDonald and Osuj, 1995; Henneberry, 1998; O Sullvan, 2000; Mkelbank, 2004; Ho and Wong, 2007; L et al., 2012b). Accordngly, ntroducton of a new major road may change a cty s household resdental locaton choces and resdental dstrbuton, whch can n turn affect the travel demand on the urban road network and thus the local authortes decsons regardng whether to ntroduce new major roads nto the system. Therefore, the effects that a new transportaton nfrastructure wll have on a cty s household resdental locaton choces, land values and housng market must be consdered n the plannng and desgn of new radal major roads of urban systems. 3

5 To account for these effects n the urban plannng, ths paper proposes an analytcal model for nvestgatng the desgn ssue of the densty (or number) of radal major roads n a two-dmensonal monocentrc cty (not necessarly symmetrc), as shown n Fg. 1. Ths paper makes two major extensons to the related lterature. Frst, an urban system equlbrum problem s formulated to model the nteractons among the followng four types of agents: local authortes, property developers, households and household workers (.e., commuters). The traffc congeston effects on the radal major roads are explctly consdered, and the household resdental dstrbuton and land values across the cty along wth the structure of the housng market n terms of housng prces and space can endogenously be determned. A heurstc soluton procedure s also presented to solve the urban system equlbrum problem. Second, a system optmum model for optmzng the densty of radal major roads s proposed to maxmze the urban system s total socal welfare. Wth use of the proposed model, numercal comparatve statc analyses of congeston prcng and road nfrastructure nvestment (.e. addng a new radal major road) are conducted. In addton, the effects of road level of servce (LOS), urban populaton sze and household ncome level on the urban system are also examned. The remander of ths paper s organzed as follows. The next secton descrbes the model s basc assumptons. Secton 3 formulates the equlbrum of the urban system, whch ncludes the commuters route choce equlbrum, the household resdental locaton choce equlbrum and the housng demand-supply equlbrum. A heurstc soluton approach s developed to solve the urban system s equlbrum problem. Secton 4 proposes a system optmum model for optmzng the densty of radal major roads n a two-dmensonal monocentrc cty. Secton 5 uses a numercal example to llustrate the applcatons of the proposed model. In partcular, comparatve statc analyses of some polcy parameters are conducted. Fnally, Secton 6 concludes the paper and provdes recommendatons for further study. 2. Basc assumptons To facltate the presentaton of essental deas wthout loss of generalty, ths paper makes the followng basc assumptons. 4

6 A1 The urban system s assumed to be a radal, closed and monocentrc cty, n whch the total populaton or number of households s exogenously gven and fxed and all job opportuntes are located n a hghly compact cty center or CBD. It s further assumed that all of the land wthn the cty boundary s owned by absentee landlords and that the value of the land at/beyond the cty boundary s equal to the agrcultural rent or opportunty cost of the land. These assumptons have been wdely adopted n the feld of urban economcs (e.g., Alonso, 1964; Muth, 1969; Mlls, 1972; Fujta, 1989; O Sullvan, 2000; Kraus, 2006; McDonald, 2009). A2 There are four types of agents n the urban economy: local authortes, property developers, households and commuters. Local authortes am to optmze the densty (or number) of radal major roads n the cty to maxmze the urban system s total socal welfare. The property developers determne the ntensty of ther captal nvestment n the land market to maxmze the net proft generated by the supply of housng. Each property developer s assumed to adopt Cobb-Douglas behavor for the housng producton functon (e.g., Beckmann, 1974; Qugley, 1984; Brueckner, 2007). A3 All households are assumed to be homogeneous, mplyng that the ncome level and utlty functon are dentcal for all households. Each household has a Cobb-Douglas utlty functon and the household ncome s spent on transportaton, housng and non-housng goods. The objectve of each household s to maxmze ts own utlty by choosng the optmum resdental locaton, area of housng space and amount of other goods wthn the household s budget constrants (e.g., Solow, 1972, 1973; Beckmann, 1969, 1974; Anas, 1982; Fujta, 1989). A4 Smlar to Anas and Moses (1979), D Este (1987) and Wong (1994), t s assumed that commuters travelng from ther home locatons to workplaces n the CBD frst travel along the mnor rng road that passes ther partcular home locatons to reach a radal major road, and then proceed along the major road to reach the cty center, whch consttutes a rng-radal routng system (see Fg. 1). It s also assumed that each commuter chooses the rng-radal route that mnmzes hs/her travel cost, thereby leadng to a Wardrop s user equlbrum for route choce. A5 Ths paper manly focuses on the commuters journeys between ther homes and ther 5

7 workplaces, whch are compulsory (or oblgatory) trps. The average number of commuters (or workers) per household s assumed to be exogenously gven and fxed, and s represented as. Every day, each worker completes one two-way commutng journey between hs/her place of resdence and a workplace located n the CBD. Thus, the average daly number of trps to the CBD per household s. For example, 1 ndcates that each household makes an average of one trp to the CBD per day. The assumpton that there s one commuter per household has also been adopted n prevous related studes (e.g., Anas and Xu, 1999; Song and Zenou, 2006; L et al., 2012a,b,c). 3. Equlbrum of the urban system Accordng to A2, there are four types of agents n the urban system: local authortes, property developers, households and commuters. The nteractons among these agents lead to a number of nterrelated equlbra: the commuters rng-radal route choce equlbrum, the household resdental locaton choce equlbrum and the housng demand-supply equlbrum. We formulate these respectve equlbra n the followng subsectons Commuters route choce equlbrum Travel cost As shown n Fg. 1, represents the th radal major road and M s the total number of radal major roads n the cty. Let x be the radal dstance of a locaton from the CBD and the angle of a locaton from the nearest radal road. The travel cost from locaton ( x, ) to the CBD va radal major road s defned as ( x, ), whch conssts of the tme and monetary costs of travel on the rng-radal routng system,.e., ( x, ) T( x, ) C ( x, ), (1) where T( x, ) and C ( x, ) are the travel tme and the monetary cost from locaton ( x, ) to the CBD va radal major road, respectvely. s the value of travel tme, whch s used to convert the travel tme nto equvalent monetary unts. 6

8 Accordng to A4, the travel tme T( x, ) conssts of the tme taken to travel dstance x from the CBD along radal major road and the tme taken to travel a crcular arc wth a length of x along the mnor rng road at dstance x from the CBD. Ths s represented as x T( x, ) T( x), (2) V 0 where T ( x ) s the tme requred to travel dstance x from the CBD on radal major road and V 0 s the average vehcle travel speed on the mnor rng road. Travel tme ( ) T x depends on the level of traffc congeston on radal road. Let t Q( x ) be the travel tme per unt of dstance around locaton x on radal road, where Q ( x ) s the traffc volume (.e., the number of commuters) at locaton x on radal road. ( ) t Q x s assumed to be a strctly ncreasng functon of traffc volume Q ( x ) at locaton x and can be estmated usng the followng Bureau of Publc Roads (BPR) functon Q ( x) tq( x) t0 1.0a1 K a2, (3) where t 0 s the free-flow travel tme per unt of dstance on radal road, of radal road and a 1 and a 2 are postve parameters. K s the capacty Hence, T ( x ) can be expressed as x T( x) t Q( w) dw 0, (4) where t ( ) can be calculated usng Eq. (3). The monetary cost C ( x, ) s assumed to be a lnear functon of the dstance traveled, as assumed n Wang et al. (2004) and Lu et al. (2009),.e., C ( x, ) c c xc x, (5) where c 0 s the fxed cost of travel (e.g., the parkng charge n the CBD per work trp) and c 1 and 2 c are the varable costs (e.g., fuel cost per unt of dstance) of travel on the radal and rng roads, respectvely. 7

9 Remark 1. (Propertes of the travel cost functon). The frst-order partal dervatves of ( x, ) wth regard to x and, respectvely, are gven by ( x, ) T( x, ) C( x, ) tq( x) c1c2 0 x x x V0 and (6) ( x, ) x c 2x0. (7) V 0 Therefore, for a gven, ( x, ) s a strctly ncreasng functon of the dstance between x and the CBD. For a gven x, ( x, ) s a strctly ncreasng functon of. Ths mples that the travel cost ncreases outwardly n the drecton of the radal major road extensons and away from the radal major roads along the mnor rng roads Boundary contour As Fg. 1 shows, two adjacent alternatve radal major roads n the two-dmensonal monocentrc cty, and +1, compete for travel demand. A watershed boundary exsts that dvdes the area between these adjacent radal roads nto two sub-areas. The watershed boundary s also called market area boundary n Anas and Moses (1979). For presentaton purposes, we defne B as the boundary contour, whch dvdes the travel demand between and +1 nto those who use and those who use +1, as shown n Fg. 1. Accordng to A4, when an equlbrum state s reached no commuter n the cty has an ncentve to change hs/her choce of radal major road when travelng to the CBD. Ths means that the cost of travelng from pont B on the boundary contour to the CBD usng radal roads and +1 s dentcal. The travel choce equlbrum can be mathematcally expressed as ( x, ˆ ) ( x, ˆ ), (8) 1 where ˆ ( x) s the angle between major road and boundary contour B at dstance x from the CBD and s the angle between radal major roads and +1. From Eqs. (1) and (8), one obtans xˆ ( x ) ˆ x ( ) 2 ( ) 1( ) ˆ ( ) 2 ˆ T x c x x T x x c x ( x) V. (9) 0 V0 Thus, ˆ ( x) can be expressed as 8

10 ˆ V ( x ) T ( x ) T ( x ), (10) 2 2x c V where T ( x ) can be determned by Eq. (4). The boundary contours B1, B2,..., B M can be determned by Eq. (10). The catchment area of radal major road s the sector bounded by B 1 and B. Remark 2. (Property of angle ˆ ). Suppose that the varable travel cost c 2 on any rng road s a constant (.e. c 2 c2 n Eq. (5)), we then have sdes of Eq. (10) from = 1 to M yelds ˆ V ( x ) T ( x ) T ( x ) M M x M1 1 cv M 1 ˆ ( x ). In fact, summng both. (11) Note that TM 1( x) T1( x) holds for a crcular cty. Therefore, Eq. (11) can be reduced to M Note that M 1 M ˆ ( ) x 2. (12) 1 1 ˆ ( x ). M 1 2. Substtutng t nto the above equaton, one mmedately obtans Remark 2 reveals that the traffc flows on the radal major roads are nterdependent; that s, an ncrease n the flow on one radal road leads to a decrease n the flow on another. It should be ponted out that the free-flow travel tmes and capactes (.e., t 0 and K n Eq. (3)) may change across the radal major roads due to the roads varyng geometres, sght dstances and servce levels. Thereby, ˆ ( x) 2 cannot hold. However, when a cty s served by evenly spaced radal roads wth the same free-flow travel tmes and capactes, as assumed n D Este (1987), then the cty s structure s entrely symmetrcal. 2 Remark 3. If the radal major roads n a cty are evenly dstrbuted (.e., 1, M 1,2,..., M ) and have dentcal travel tme functons (.e., t 0 t ( 1)0 and K K 1, 1,2,..., M ), then ˆ ( x). 2 M 9

11 Travel demand for each radal major road Let qx (, ) be the hourly densty of travel demand (.e., the number of commuters per unt of land area) at locaton ( x, ), be the average number of daly trps to the CBD per household and be the peak-hour factor (.e., the rato of peak-hour flow to the average daly flow), whch s used to convert the travel demand from a daly to an hourly bass. qx (, ) can then be defned as qx (, ) nx (, ) nx (, ), (13) where ( ) s the average number of peak hour trps to the CBD per household and nx (, ) s the household resdental densty at locaton ( x, ), whch s defned later. The hourly travel demand Q ( x ) at locaton x on radal major road can thus be gven by x ˆ ( ) ˆ w x ( w) Q ( x ) q ( w, ) wddw n ( w, ) wddw, (14) x ( ˆ ˆ 11( w)) x ( 11( w)) where x s the dstance from the cty boundary to the CBD (or the cty length) along radal road and ˆ s gven by Eq. (10). The frst-order dervatve of Q ( x ) wth regard to x s dq ( x) xn( x, ) d. (15) ˆ ( x ) ( ˆ dx 11( x)) dq ( x) Ths mples that 0. The travel demand functon Q ( x ) s therefore a decreasng dx functon of dstance x from the CBD. Remark 4. In vew of the above, once the household resdental densty nx (, ) s known, one can then determne the travel demand Q ( x ) by Eq. (14) or (15), the travel tme T ( x ) by Eq. (4), the travel cost ( x, ) by Eq. (1) and the boundary contour set M or, equvalently, the crtcal angle set ˆ ( x ), 1,2,..., M B, 1, 2,..., (10). n terms of Eq. 10

12 3.2. Housng market equlbrum Household resdental locaton choce behavor To model household resdental locaton choce behavor, we frst defne the household utlty functon. In ths paper, the followng Cobb-Douglas form of the household utlty functon s adopted U( x, ) z( x, ) g( x, ),, 0, 1, (16) where U( x, ) s the utlty functon of households at locaton ( x, ), and are postve constants, zx (, ) s the composte non-housng goods consumed per household at locaton ( x, ), for whch the prce s normalzed to 1, and gx (, ) s the average consumpton of housng per household at locaton ( x, ), whch s measured n square meters of floor space. Accordng to A3, t s assumed that each household chooses the resdental locaton that maxmzes ts own utlty, subject to budget constrants. The household utlty maxmzaton problem can be represented as max U( x, ) z( x, ) g( x, ), (17) zg, s.t. zx (, ) px (, ) gx (, ) YEx (, ), (18) where px (, ) s the average annual rental prce per unt of housng floor area at locaton ( x, ), Y s the average annual household ncome and Ex (, ) s the average annual travel cost (or expendture) from locaton ( x, ) to the CBD along the rng-radal routng system, whch can be measured by Ex (, ) 2 ( x, ), (19) where the 2 denotes a round-trp journey between locaton ( x, ) and the CBD and s the average annual number of trps to the CBD per household. The (one-way) average travel cost, ( x, ), from locaton ( x, ) to the CBD can be determned by Eq. (1). Substtutng zx (, ) n Eq. (18) nto Eq. (17) and settng the dervatve of U ( ) wth regard to g equal to zero (.e., du dg 0 ), one obtans 11

13 Y E( x, ) gx (, ) px (, ). (20) When the household resdental locaton choce equlbrum state s reached, all households n the cty have the same utlty level regardless of ther resdental locatons. Let u be the common utlty level. The followng equaton then holds u z( x, ) g( x, ) Y E( x, ) p( x, ) g( x, ) g( x, ), (21) where g() and p() can be derved from Eqs. (20) and (21) as functons of the common utlty level u, as follows: 1 gx (,, u) YEx (, ) u and (22) 1 1 p( x,, u) Y E( x, ) u. (23) Eqs. (22) and (23) descrbe the equlbrum amount of housng floor space per household and the equlbrum prce per unt of housng floor space, respectvely, at locaton ( x, ). These equatons show that for a gven level of utlty, the average housng prce decreases and the average housng floor space per household ncreases as the travel cost ncreases, and vce versa Property developers housng producton behavor Ths subsecton focuses on the supply sde of the housng market. In ths paper, property developers are assumed to behave n keepng wth the followng Cobb-Douglas form of the housng producton functon S x h S( x, ) (, ) b, 0 b 1, (24) where (, ) h S x s the housng supply per unt of land area at locaton ( x, ), S( x, ) s the captal nvestment per unt of land area at locaton ( x, ) (also referred to as captal nvestment ntensty) and and b are postve parameters. Let rx (, ) be the rent or value per unt of land area at locaton ( x, ) and k be the prce of captal (.e., the nterest rate). The net proft per unt of land area, ( x, ), at locaton ( x, ) can then be gven by 12

14 ( x, ) p( x, ) h S( x, ) r( x, ) ks( x, ), (25) where the prce per unt of housng floor space p( ) s gven by Eq. (23). The frst term on the rght-hand sde of Eq. (25) s the total revenue from housng leases. The fnal two terms are the land rent cost and the captal cost, respectvely. From A2, each property developer n the housng market ams to maxmze hs/her own net proft by determnng the optmal captal nvestment ntensty, whch s expressed as b max ( x, ) px (, ) S rx (, ) ks. (26) S The frst-order optmalty condton of the maxmzaton problem (26) yelds px bs k S b1 (, ) 0. (27) Substtutng p( ) n Eq. (23) nto Eq. (27) produces the captal nvestment ntensty as a functon of the utlty level u,.e., b Sx (,, u) YEx (, ) u bk. (28) The household resdental densty nx (, ) at locaton ( x, ) can thus be calculated by 1(1 b) 1 1 ( b) h S( x,, u) nx (, ) bk u YEx (, ) gx (,, u) b ( b) ( b). (29) Note that under perfect competton, the property developers earn zero proft, thus b rx (, ) px (, ) Sx (, ) ksx (, ). (30) Substtutng Eqs. (23) and (28) nto Eq. (30) yelds rx (,, u) k 1 YEx (, ) u bk b b. (31) Eqs. (28), (29) and (31) defne the equlbrum captal nvestment ntensty, resdental densty and land value at any locaton wthn the cty, respectvely. It can be seen that gven the utlty level u, the captal nvestment ntensty, resdental densty and land value all decrease as ether the travel cost or the nterest rate ncreases, and vce versa. 13

15 Housng demand-supply equlbrum Balancng the housng supply and demand requres that all households ft exactly nsde the cty boundary,.e., M 1 ˆ x( ) nx (, ) xdxd N, (32) ( ˆ 11) 0 where N s the total number of households n the cty. The left-hand sde of Eq. (32) s the sum of the number of households n the catchment areas for all of the radal major roads wthn a cty. The equlbrum rent per unt of land area devoted to housng at the cty frnge ( x, ) equals the exogenous agrcultural rent or the opportunty cost of the land; that s, rx ( ( ),, u) r, (33) where r a s a constant agrcultural rent. a Usng Eq. (31), Eq. (33) can be rewrtten as (, ) b k Y E x u bk ra. (34) b Remark 5. Eqs. (32) and (34), together wth Eqs. (22), (23), (28), (29) and (31), determne the housng market equlbrum. Gven the travel cost Ex (, ) or ( x, ) (see Eq. (19)), one can determne the values of household utlty level u and the cty boundary x by solvng the system of Eqs. (32) and (34) and thus the followng functons: gx (, ), px (, ), S( x, ), nx (, ) and rx (, ) Calculatng the equlbrum soluton for the urban system In ths subsecton, a procedure for calculatng the equlbrum soluton of the urban system s presented. Gven the household resdental densty nx (, ), the commuters route choce equlbrum problem can determne the functons Q ( x ), T ( x ) and ( x, ) n addton to the boundary contours B, 1, 2,..., M. In contrast, gven the travel cost ( x, ), the 14

16 housng market equlbrum problem can determne the functons nx (, ), gx (, ), px (, ), S( x, ) and rx (, ) and the constants u and x. The nterdependence of the nterrelated equlbra leads to a statonary soluton wth regard to resdental densty and travel costs, as follows: n (0) ψ (0) n (1) ψ (1) n *, ψ *, (35) where the bolded symbols represent the vectors of the correspondng varables; that s, ψ ( x, ) and nx (, ) n. The step-by-step procedure for determnng the (statonary) equlbrum soluton of the urban system s as follows. Step 1. Choose ntal values for the household resdental densty travel demand vector (0) Q (0) ( ) x vector (0) T (0) ( ) x (0) n, then determne the Q n terms of Eqs. (13) and (14), the travel tme T by Eq. (4), the travel cost vector crtcal angle vector ˆ (0) ˆ (0) ( ) x (0) ψ by Eq. (1) and the θ accordng to Eq. (10). Set the teraton counter to l 1. Step 2. Solvng the system of Eqs. (32) and (34) yelds the values of () l () u and x l. The values of the vectors g () l, substtutng () l () u and l () l p, () l S, () l n and () l r can then be obtaned by x nto Eqs. (22), (23), (28), (29) and (31). Step 3. Determne the travel demand vector () l Q n terms of Eqs. (13) and (14) and the travel tme vector () l T accordng to Eq. (4). The auxlary travel cost vector ψ () l can then be obtaned by Eq. (1) and thus, the crtcal angle vector l. ( Step 4. Update the travel cost accordng to l 1) ( ) ( ) ( ) ψ ψ l ψ l ψ l ˆ () θ l by Eq. (10). Step 5. If the relatve gap ( 1) ( ) ( ) l l / l ψ ψ ψ s smaller than a pre-specfed tolerance, then stop. Otherwse, set l l 1 and go to Step 2. In Step 1, the ntal household resdental densty can be assumed to be unform across ths cty. In Step 2, the system of Eqs. (32) and (34) can be solved usng an teratve method n whch the decson varables x and u are sequentally updated whle holdng the value of 15

17 the other varable fxed. Specfcally, one chooses ntal values for x, then solves Eq. (32) to obtan the value of u. The values of x can then be updated by solvng Eq. (34) usng the b-secton method for the value of u that has just been obtaned. Repeatng the teratve process yelds the solutons for x and u. 4. Model for optmzng the densty of radal major roads As prevously stated, local authortes am to maxmze the total socal welfare (SW) of the urban system by optmzng the densty of the radal major roads wthn the two-dmensonal monocentrc cty. The socal welfare, whch takes nto account the benefts of all partes n the urban system, s defned as the total utlty of all households plus the aggregate rent receved by the absentee landlords mnus the total road nvestment cost. The socal welfare maxmzaton problem can be formulated as M ˆ x( ) M ( ˆ 1 1) 0 a, (36) 1 1 max SW= un + r( x, ) r xddx M where s a parameter that converts the utlty level of households nto the equvalent monetary unts. rx (, ) can be determned usng the equlbrum formulaton of the urban system proposed n the prevous secton. represents the constructon cost of radal major road. The frst term on the rght-hand sde of Eq. (36) denotes the total utlty of all households, the second term denotes the aggregate rent receved by the absentee landlords, and the thrd term denotes the total constructon cost of all radal major roads. It s assumed that the constructon cost, to the length, x, of radal road and ts capacty, of radal major road s a functon wth respect K, as follows: xk, (37) where s a postve constant. Eq. (37) ndcates that the road constructon cost s proportonal to the road length and wdth. Note that the model (36) s an nteger programmng problem wth the number of radal major roads as the decson varable. In general, ths type of problem s dffcult to solve (L et al., 2011, 2012c). Fortunately, the number of radal major roads n a cty s fnte. Therefore, a 16

18 smple approach to determne the optmal densty of radal major roads s to compare the resultant values of objectve functon (36) usng dfferent numbers of radal major roads. 5. Model applcatons In ths secton, a numercal example s gven to llustrate the applcatons of the proposed model and the contrbutons of ths paper. The numercal example s ntended to ascertan the effects of road level of servce (LOS), urban populaton sze (number of households) and household ncome level on the optmal densty of the radal major roads and the performance of the urban system. It s also used to nvestgate the effects of varous urban polces, such as congeston prcng and road nfrastructure nvestment (ntroducng a new radal major road) on the urban economy. In order to quanttatvely evaluate the effects of congeston prcng scheme and addng a new radal major road, some performance measures are defned as follows: Cty area (or sze) = ˆ M x( ) xdxd 1 ( ˆ 11), (38) 0 Average household resdental densty = N cty area, (39) Average housng space per famly = ˆ x( ) M gx (, ) nx (, ) xdxd N, (40) 1 ( ˆ 11) 0 Average housng prce = ˆ x( ) M px (, ) xdxd cty area, (41) 1 ( ˆ 11) 0 Average land value = ˆ x( ) M rx (, ) xdxd cty area, (42) 1 ( ˆ 11) 0 Average captal nvestment ntensty = ˆ x( ) M S( x, ) xdxd cty area. (43) 1 ( ˆ 11) 0 For presentaton purposes, n the numercal experment, all of the radal major roads n the cty are assumed to have dentcal free-flow travel tmes and capactes. The baselne values (.e. base case) for the model s nput parameters are shown n Table 1. In the followng analyss, unless specfcally stated otherwse, the nput data are dentcal to those of the base case. The computer code for the numercal experment (wrtten n programmng language C) s not shown n the paper so as to save space, but avalable from the authors on request Effects of road LOS, urban populaton sze, and household ncome level on densty of 17

19 radal major roads We frst nvestgate the effects of the road LOS, number of households (or populaton sze), and household ncome level on the optmal densty of the radal major roads. Fg. 2 plots the contour of the annual total socal welfare of the urban system n the space of the road LOS (.e. road capacty) and the number (or densty) of radal major roads. It can be seen that for a gven road capacty, as the densty of the major roads ncreases, the annual total socal welfare of the urban system frst ncreases and then decreases. The maxmum socal welfare for a gven road capacty (or LOS) occurs at the pont of tangency between the horzontal lne passng through the gven road capacty and the socal welfare contour. For example, the horzontal lne wth the road capacty of 4950 vehcles per hour touches a socal welfare contour at pont F, as shown n Fg. 2. Ths means that when the road capacty s 4950 vehcles per hour, the optmal number of the radal major roads s 7. Any pont on the dotted curve n Fg. 2 represents the maxmum socal welfare for a gven road LOS. It can also be seen that as the road capacty (or LOS) ncreases, the optmal number of the radal major roads decreases, and vce versa. Fg. 3 dsplays the change of the annual total socal welfare of the urban system wth the total number of households and the number (or densty) of the radal major roads. It can be seen that for a gven number of households, the assocated horzontal lne touches a socal welfare contour, mplyng that there s an optmal number of the radal roads. For nstance, when the number of households s 300,000, the optmal number of the radal roads s 8. The dotted curve n Fg. 3 defnes the maxmum socal welfare levels for dfferent numbers of households. It shows that as the number of households (or populaton sze) grows, the optmal number of the radal roads ncreases. Fg. 4 ndcates the change of the annual total socal welfare of the urban system wth the household ncome level and the number of radal major roads. It can be observed that the optmal number of the radal major roads would be 7 regardless of the household ncome level. Ths mples that the household ncome level has no apparent effect on the optmal densty of the radal major roads Effects of optmal congeston prcng on densty of radal major roads 18

20 In the lterature, congeston prcng schemes generally nclude frst-best scheme, cordon-based scheme, and dstance-based scheme (see Mtchell et al., 2005; L et al., 2012a). The frst-best and cordon-based schemes have been wdely explored n the feld of urban economcs (for more detals, see Mun et al., 2003; Verhoef, 2005; Anas and Rhee, 2006; L et al., 2012a; De Lara et al., 2013). Here, we nvestgate the effects of the dstance-based congeston prcng scheme on the optmal densty of the radal major roads. The dstance-based prcng scheme mples that the toll s proportonal to the dstance traveled, that s, the product of the travel dstance and the toll per unt of dstance. Fg. 5 depcts the contour of the annual total socal welfare of the urban system n the toll-road densty space. It can be seen that the maxmum socal welfare occurs at the toll level of $0.36 per klometer and 6 major roads, causng a socal welfare of $ bllon per year (see Table 2). Table 2 summarzes the effects of the congeston prcng scheme on the urban system. It can be seen that mplementaton of the congeston prcng scheme causes a decrease n the cty sze (or cty area) by 234 square klometers (from to square klometers). Ths s because the addtonal tolls under the dstance-based congeston prcng scheme ncrease the annual transportaton expendtures of households and thus lead them to move towards the cty center. As a result, the average resdental densty, average housng prce, average captal nvestment ntensty, and average land value ncrease by 90 households per square klometer, $92.3 per square meter, $25.4 mllon per square klometer, and $0.6 mllon per square klometer, respectvely. However, the average housng space per household decreases by 0.6 square meter. In addton, t can also be seen that the congeston prcng scheme leads to a decrease n the household utlty level by 4.6 utlty unts due to an ncreased travel cost, and n road constructon cost by $55.8 mllon due to a reduced cty sze, but the aggregate land rent ncreases by $62.8 mllon due to an ncreased land value. As a result, the annual socal welfare of the urban system ncreases by $18.8 mllon (from $ to $ mllon) Effects of a new addtonal radal major road on urban system In ths subsecton, we address the followng two problems: (1) where s optmal locaton of a new addtonal radal major road? (2) What are the effects of a new addtonal radal major road on the urban system? For llustraton purposes, we consder a cty wth fve exstng radal major roads, whch are numbered as 1, 2, 3, 4, and 5, respectvely, as shown n bolded lnes n Fg. 6. The angles among the fve radal major roads are 120, 40, 50, 60, and 90, 19

21 respectvely Optmal locaton of a new addtonal radal road In order to determne the optmal locaton of a new addtonal radal major road n the cty shown n Fg. 6, Fg. 7 depcts the annual socal welfare curves when the new addtonal radal road s located between any two exstng radal roads, respectvely. In Fg. 7, represents to nsert the new addtonal radal road n between roads and j. It can be seen n ths fgure that the optmal locaton of the new addtonal radal road should be located between radal roads 1 and 2 wth 0.92 radan (.e ) from the radal road 1 (shown n dotted lne n Fg. 6), whch results n the maxmum socal welfare level of $ bllon per year. R j Comparson of urban system performances before and after addng a new radal road Fnally, we examne the effects of an addtonal radal road (shown n Fg. 6) on the urban system. Fgs. 8a-d and 8a'-d' plot the contours of the household resdental densty, housng prce, housng space per household, and captal nvestment ntensty across the cty before and after ntroducng a new radal road, respectvely. It can be seen that ntroducton of a new radal road leads to a change n the urban shape from a pentagram (.e. a fve-ponted star) to a hexagram (.e. a sx-ponted star). In the meantme, t also leads to a decrease n the household resdental densty, the housng prce, and the captal nvestment ntensty, but an ncrease n the housng space per household. Specfcally, the household resdental denstes on the cty boundary and n the cty center decrease by 0.5 (from 61 to 60.5) and 648 (from 3992 to 3344) households per square klometer respectvely, as shown n Fgs. 8a and a'. The housng prces on the cty boundary and n the cty center (shown n Fgs. 8b and b') decrease by $3 (from $1248 to $1245) and $250 (from $4836 to $4586) per square meter, respectvely. The housng spaces per household on the cty boundary and n the cty center (see Fgs. 8c and c') ncrease by 0.18 (from to 13.42) and 0.26 (from 4.79 to 5.05) square meter, respectvely. The captal nvestment ntenstes on the cty boundary and n the cty center decrease by $0.1 (from $14.2 to $14.1) and $211 (from $1295 to $1084) mllon per square klometer respectvely, as shown n Fgs. 8d and d'. 20

22 Table 3 further summarzes the effects of addng a new radal road on the performance of the urban system. It shows that ntroducton of a new radal road ncreases the sze of the cty by 87.8 square klometers and the average housng space per household by 0.2 square meter. However, t also decreases the average household resdental densty from to households per square klometer, the average housng prce from $ to $ per square klometer, the average land value from $2.6 to $2.5 mllon per square klometer, and the average captal nvestment ntensty from $122.7 to $114.7 mllon per square klometer, respectvely. As a result, the household utlty level ncreases 2.7 utlty unts, the total land rent decreases by $8.3 mllon, the road constructon cost ncreases by $70 mllon, and the annual socal welfare ncreases by $29 mllon. 6. Concluson and further studes Ths paper nvestgated the desgn problem of the densty of radal major roads n a two-dmensonal monocentrc cty. The urban system concerned ncluded four types of agents: local authortes, property developers, households and commuters. The nterdependence among these agents nduces a number of nterrelated equlbra; namely, the housng demand-supply equlbrum, household resdental locaton choce equlbrum and commuters rng-radal route choce equlbrum. Based on the urban system equlbrum analyss, a heurstc soluton approach was developed to solve the urban system s equlbrum problem and a system optmum model was proposed to determne the optmal densty of the radal major roads so as to maxmze the urban system s socal welfare. In the proposed model, the household resdental dstrbuton, captal nvestment ntensty, land values, housng prces and housng space can all be endogenously determned. An llustratve numercal example was gven to assess the effects of road level of servce (LOS), urban populaton sze and household ncome level on the optmal densty of the radal major roads. The comparatve statc analyses of the congeston prcng and road nfrastructure nvestment were also carred out. The proposed model can be served as a useful tool for the long-term strategc plannng of sustanable urban developments and for evaluaton of varous transportaton, land-use and housng polces. The proposed model offers some new nsghts and nterestng fndngs. Frst, the road capacty (or LOS) and the number of households (or populaton sze) have a sgnfcant effect 21

23 on the optmal densty (or number) of the radal major roads. Specfcally, the optmal number of the radal major roads ncreases wth the ncrease of the number of households but decreases wth the ncrease of the road LOS. However, the household ncome level may have lttle mpact on the optmal densty of the radal roads. Second, congeston prcng scheme can decrease the sze of cty and thus lead to a more compact cty. It can also ncrease the socal welfare of the urban system and save the government s nvestment on road nfrastructure projects at the expense of the household utlty. Thrd, the ntroducton of an addtonal radal major road can ncrease the sze of cty and thus cause a more decentralzed cty. Households and the whole urban system can beneft from the road nfrastructure nvestment that s funded by the government. Although the modelng methodology proposed n ths paper provdes a new avenue for modelng the nteractons among land use, housng market and transportaton nfrastructure mprovements, further extensons are necessary. Frst, the cty of nterest was assumed to be monocentrc n ths paper. However, modern ctes generally have multple busness and commercal centers. Therefore, further studes could mprove the model by shftng from a monocentrc cty to a polycentrc structure (Wong, 1998; Kloosterman and Musterd, 2001; Yn et al., 2013; Ho et al., 2013). Second, ths paper focused manly on the auto mode, thus gnorng the competton and substtuton effects between auto and transt modes. To ncorporate the nteracton and competton between dfferent transportaton modes, the sngle-mode system should be extended nto a mult-modal system (Capozza, 1976; Anas and Moses, 1979; L et al., 2012a). Thrd, all of the households n ths paper were assumed to be homogenous. However, an emprcal study by Kwon (2003) showed that household ncome level may affect resdental locaton choce. Therefore, future models should be extended to consder the choce behavor of households wth dfferent ncome levels and demographc characterstcs. Acknowledgments The authors would lke to thank the edtor, Professor Yves Zenou, and two anonymous referees for ther helpful comments and suggestons on an earler draft of the paper. The work descrbed n ths paper was jontly supported by grants from the Natonal Natural Scence Foundaton of Chna ( , ), the Research Foundaton for the Authors of 22

24 Natonal Excellent Doctoral Dssertatons (Chna) (200963), the Doctoral Fund of Mnstry of Educaton of Chna ( ), and the Fok Yng Tung Educaton Foundaton (132015). References Alonso, W., Locaton and land use: toward a general theory of land rent. Massachusetts: Harvard Unversty Press, Cambrdge. Anas, A., Resdental locaton markets and urban transportaton. New York: Academc Press. Anas, A., Moses, L.N., Mode choce, transport structure and urban land use. Journal of Urban Economcs, 6 (2), Anas, A., Rhee, H.J., Curbng excess sprawl wth congeston tolls and urban boundares. Regonal Scence and Urban Economcs, 36 (4), Anas, A., Xu, R., Congeston, land use, and job dsperson: a general equlbrum model. Journal of Urban Economcs, 45 (3), Baum-Snow, N., Suburbanzaton and transportaton n the monocentrc model. Journal of Urban Economcs, 62 (3), Beckmann, M.J., On the dstrbuton of urban rent and resdental densty. Journal of Economc Theory, 1 (1), Beckmann, M.J., Spatal equlbrum n housng market. Journal of Urban Economcs, 1 (1), Brueckner, J.K., Urban growth boundares: an effectve second-best remedy for unprced traffc congeston? Journal of Housng Economcs, 16 (3-4), Capozza, D.R., Land use n a cty wth two modes of transportaton. Southern Economc Journal, 42 (3), De Lara, M., de Palma, A., Klan, M., Pperno, S., Congeston prcng and long term urban form: Applcaton to Pars regon. Regonal Scence and Urban Economcs, 43 (2), D Este, G., Trp assgnment to radal major roads. Transportaton Research Part B, 21 (6), Fujta, M., Urban economc theory. Cambrdge: Cambrdge Unversty Press. Henneberry, J., Transport nvestment and house prces. Journal of Property Valuaton 23

25 and Investment, 16 (2), Ho, H.W., Wong, S.C., Housng allocaton problem n a contnuum transportaton system. Transportmetrca, 3 (1), Ho H.W., Wong S.C., Sumalee, A., A congeston-prcng problem wth a polycentrc regon and mult-class users: a contnuum modelng approach. Transportmetrca, n press. DOI: / Kloosterman, R.C., Musterd, S., The polycentrc urban regon: towards a research agenda. Urban Studes, 38 (4), Kraus, M., Monocentrc ctes. In Arnott, R. J., McMllan, D. P. (Eds.), A Companon to urban economcs (pp ). Oxford: Blackwell Publshng. Kwon, Y., The effect of a change n wages on welfare n a two-class monocentrc cty. Journal of Regonal Scence, 43 (1), L, Z.C., Lam, W.H.K., Wong, S.C., On the allocaton of new lnes n a compettve transt network wth uncertan demand and scale economes. Journal of Advanced Transportaton, 45 (4), L, Z.C., Lam, W.H.K., Wong, S.C., 2012a. Modelng ntermodal equlbrum for bmodal transportaton system desgn problems n a lnear monocentrc cty. Transportaton Research Part B, 46 (1), L, Z.C., Lam, W.H.K., Wong, S.C., Cho, K., 2012b. Modelng the effects of ntegrated ral and property development on the desgn of ral lne servces n a lnear monocentrc cty. Transportaton Research Part B, 46 (6), L, Z.C., Lam, W.H.K., Wong, S.C., Sumalee, A., 2012c. Desgn of a ral transt lne for proft maxmzaton n a lnear transportaton corrdor. Transportaton Research Part E, 48 (1), Lu, T.L., Huang, H.J., Yang, H., Zhang, X., Contnuum modelng of park-and-rde servces n a lnear monocentrc cty wth determnstc mode choce. Transportaton Research Part B, 43 (6), McDonald, J.F., Calbraton of a monocentrc cty model wth mxed land use and congeston. Regonal Scence and Urban Economcs, 39 (1), McDonald, J.F., Osuj, C.I., The effect of antcpated transportaton mprovement on resdental land values. Regonal Scence and Urban Economcs, 25 (3), Mkelbank, B.A., Spatal analyss of the relatonshp between housng values and nvestments n transportaton nfrastructure. Annals of Regonal Scence, 38 (4), Mlls, E.S., Urban economcs. Illnos: Scott Foresman, Glenvew. 24

26 Mtchell, G., Namdeo, A., Mlne, D., The ar qualty mpact of cordon and dstance based road user chargng: an emprcal study of Leeds, UK. Atmospherc Envronment, 39 (33), Muth, R.F., Ctes and housng. Chcago: Unversty of Chcago Press. Mun, S.I., Konsh, K.J., Yoshkawa, K., Optmal cordon prcng. Journal of Urban Economcs, 54 (1), O Sullvan, A., Urban economcs. Boston: Irwn/McGraw-Hll. Qugley, J.M., The producton of housng servces and the derved demand for resdental energy. RAND Journal of Economcs, 15 (4), Solow, R.M., Congeston, densty and the use of land n transportaton. Swedsh Journal of Economcs, 74 (1), Solow, R.M., Congeston cost and the use of land for streets. Bell Journal of Economcs and Management Scence, 4 (2), Song, Y., Zenou, Y., Property tax and urban sprawl: theory and mplcatons for US ctes. Journal of Urban Economcs, 60 (3), Verhoef, E.T., Second-best congeston prcng schemes n the monocentrc cty. Journal of Urban Economcs, 58 (3), Wang, J.Y.T., Yang, H., Lndsey, R., Locatng and prcng park-and-rde facltes n a lnear monocentrc cty wth determnstc mode choce. Transportaton Research Part B, 38 (8), Wong, S.C., An alternatve formulaton of D Este s trp assgnment model. Transportaton Research Part B, 28 (3), Wong, S.C., Mult-commodty traffc assgnment by contnuum approxmaton of network flow wth varable demand. Transportaton Research Part B, 32 (8), Yn, J., Wong, S.C., Sze, N.N., Ho, H.W., A contnuum model for housng allocaton and transportaton emsson problems n a polycentrc cty. Internatonal Journal of Sustanable Transportaton, 7 (4),

Pricing and Resource Allocation Game Theoretic Models

Pricing and Resource Allocation Game Theoretic Models Prcng and Resource Allocaton Game Theoretc Models Zhy Huang Changbn Lu Q Zhang Computer and Informaton Scence December 8, 2009 Z. Huang, C. Lu, and Q. Zhang (CIS) Game Theoretc Models December 8, 2009

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

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

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

Winter 2008 CS567 Stochastic Linear/Integer Programming Guest Lecturer: Xu, Huan

Winter 2008 CS567 Stochastic Linear/Integer Programming Guest Lecturer: Xu, Huan Wnter 2008 CS567 Stochastc Lnear/Integer Programmng Guest Lecturer: Xu, Huan Class 2: More Modelng Examples 1 Capacty Expanson Capacty expanson models optmal choces of the tmng and levels of nvestments

More information

Module 3 LOSSY IMAGE COMPRESSION SYSTEMS. Version 2 ECE IIT, Kharagpur

Module 3 LOSSY IMAGE COMPRESSION SYSTEMS. Version 2 ECE IIT, Kharagpur Module 3 LOSSY IMAGE COMPRESSION SYSTEMS Verson ECE IIT, Kharagpur Lesson 6 Theory of Quantzaton Verson ECE IIT, Kharagpur Instructonal Objectves At the end of ths lesson, the students should be able to:

More information

Market structure and Innovation

Market structure and Innovation Market structure and Innovaton Ths presentaton s based on the paper Market structure and Innovaton authored by Glenn C. Loury, publshed n The Quarterly Journal of Economcs, Vol. 93, No.3 ( Aug 1979) I.

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

Hila Etzion. Min-Seok Pang

Hila Etzion. Min-Seok Pang RESERCH RTICLE COPLEENTRY ONLINE SERVICES IN COPETITIVE RKETS: INTINING PROFITILITY IN THE PRESENCE OF NETWORK EFFECTS Hla Etzon Department of Technology and Operatons, Stephen. Ross School of usness,

More information

Linear Regression Analysis: Terminology and Notation

Linear Regression Analysis: Terminology and Notation ECON 35* -- Secton : Basc Concepts of Regresson Analyss (Page ) Lnear Regresson Analyss: Termnology and Notaton Consder the generc verson of the smple (two-varable) lnear regresson model. It s represented

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

Economics 2450A: Public Economics Section 10: Education Policies and Simpler Theory of Capital Taxation

Economics 2450A: Public Economics Section 10: Education Policies and Simpler Theory of Capital Taxation Economcs 2450A: Publc Economcs Secton 10: Educaton Polces and Smpler Theory of Captal Taxaton Matteo Parads November 14, 2016 In ths secton we study educaton polces n a smplfed verson of framework analyzed

More information

Lecture Notes on Linear Regression

Lecture Notes on Linear Regression Lecture Notes on Lnear Regresson Feng L fl@sdueducn Shandong Unversty, Chna Lnear Regresson Problem In regresson problem, we am at predct a contnuous target value gven an nput feature vector We assume

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

NUMERICAL DIFFERENTIATION

NUMERICAL DIFFERENTIATION NUMERICAL DIFFERENTIATION 1 Introducton Dfferentaton s a method to compute the rate at whch a dependent output y changes wth respect to the change n the ndependent nput x. Ths rate of change s called the

More information

Annexes. EC.1. Cycle-base move illustration. EC.2. Problem Instances

Annexes. EC.1. Cycle-base move illustration. EC.2. Problem Instances ec Annexes Ths Annex frst llustrates a cycle-based move n the dynamc-block generaton tabu search. It then dsplays the characterstcs of the nstance sets, followed by detaled results of the parametercalbraton

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

CIE4801 Transportation and spatial modelling Trip distribution

CIE4801 Transportation and spatial modelling Trip distribution CIE4801 ransportaton and spatal modellng rp dstrbuton Rob van Nes, ransport & Plannng 17/4/13 Delft Unversty of echnology Challenge the future Content What s t about hree methods Wth specal attenton for

More information

DUE: WEDS FEB 21ST 2018

DUE: WEDS FEB 21ST 2018 HOMEWORK # 1: FINITE DIFFERENCES IN ONE DIMENSION DUE: WEDS FEB 21ST 2018 1. Theory Beam bendng s a classcal engneerng analyss. The tradtonal soluton technque makes smplfyng assumptons such as a constant

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

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

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

829. An adaptive method for inertia force identification in cantilever under moving mass

829. An adaptive method for inertia force identification in cantilever under moving mass 89. An adaptve method for nerta force dentfcaton n cantlever under movng mass Qang Chen 1, Mnzhuo Wang, Hao Yan 3, Haonan Ye 4, Guola Yang 5 1,, 3, 4 Department of Control and System Engneerng, Nanng Unversty,

More information

Numerical Heat and Mass Transfer

Numerical Heat and Mass Transfer Master degree n Mechancal Engneerng Numercal Heat and Mass Transfer 06-Fnte-Dfference Method (One-dmensonal, steady state heat conducton) Fausto Arpno f.arpno@uncas.t Introducton Why we use models and

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

Resource Allocation with a Budget Constraint for Computing Independent Tasks in the Cloud

Resource Allocation with a Budget Constraint for Computing Independent Tasks in the Cloud Resource Allocaton wth a Budget Constrant for Computng Independent Tasks n the Cloud Wemng Sh and Bo Hong School of Electrcal and Computer Engneerng Georga Insttute of Technology, USA 2nd IEEE Internatonal

More information

A Hybrid Variational Iteration Method for Blasius Equation

A Hybrid Variational Iteration Method for Blasius Equation Avalable at http://pvamu.edu/aam Appl. Appl. Math. ISSN: 1932-9466 Vol. 10, Issue 1 (June 2015), pp. 223-229 Applcatons and Appled Mathematcs: An Internatonal Journal (AAM) A Hybrd Varatonal Iteraton Method

More information

Parking Demand Forecasting in Airport Ground Transportation System: Case Study in Hongqiao Airport

Parking Demand Forecasting in Airport Ground Transportation System: Case Study in Hongqiao Airport Internatonal Symposum on Computers & Informatcs (ISCI 25) Parkng Demand Forecastng n Arport Ground Transportaton System: Case Study n Hongqao Arport Ln Chang, a, L Wefeng, b*, Huanh Yan 2, c, Yang Ge,

More information

1 The Sidrauski model

1 The Sidrauski model The Sdrausk model There are many ways to brng money nto the macroeconomc debate. Among the fundamental ssues n economcs the treatment of money s probably the LESS satsfactory and there s very lttle agreement

More information

COMPARISON OF SOME RELIABILITY CHARACTERISTICS BETWEEN REDUNDANT SYSTEMS REQUIRING SUPPORTING UNITS FOR THEIR OPERATIONS

COMPARISON OF SOME RELIABILITY CHARACTERISTICS BETWEEN REDUNDANT SYSTEMS REQUIRING SUPPORTING UNITS FOR THEIR OPERATIONS Avalable onlne at http://sck.org J. Math. Comput. Sc. 3 (3), No., 6-3 ISSN: 97-537 COMPARISON OF SOME RELIABILITY CHARACTERISTICS BETWEEN REDUNDANT SYSTEMS REQUIRING SUPPORTING UNITS FOR THEIR OPERATIONS

More information

Module 9. Lecture 6. Duality in Assignment Problems

Module 9. Lecture 6. Duality in Assignment Problems Module 9 1 Lecture 6 Dualty n Assgnment Problems In ths lecture we attempt to answer few other mportant questons posed n earler lecture for (AP) and see how some of them can be explaned through the concept

More information

An Interactive Optimisation Tool for Allocation Problems

An Interactive Optimisation Tool for Allocation Problems An Interactve Optmsaton ool for Allocaton Problems Fredr Bonäs, Joam Westerlund and apo Westerlund Process Desgn Laboratory, Faculty of echnology, Åbo Aadem Unversty, uru 20500, Fnland hs paper presents

More information

Statistics II Final Exam 26/6/18

Statistics II Final Exam 26/6/18 Statstcs II Fnal Exam 26/6/18 Academc Year 2017/18 Solutons Exam duraton: 2 h 30 mn 1. (3 ponts) A town hall s conductng a study to determne the amount of leftover food produced by the restaurants n the

More information

Uncertainty in measurements of power and energy on power networks

Uncertainty in measurements of power and energy on power networks Uncertanty n measurements of power and energy on power networks E. Manov, N. Kolev Department of Measurement and Instrumentaton, Techncal Unversty Sofa, bul. Klment Ohrdsk No8, bl., 000 Sofa, Bulgara Tel./fax:

More information

Uniqueness of Nash Equilibrium in Private Provision of Public Goods: Extension. Nobuo Akai *

Uniqueness of Nash Equilibrium in Private Provision of Public Goods: Extension. Nobuo Akai * Unqueness of Nash Equlbrum n Prvate Provson of Publc Goods: Extenson Nobuo Aka * nsttute of Economc Research Kobe Unversty of Commerce Abstract Ths note proves unqueness of Nash equlbrum n prvate provson

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

ECE559VV Project Report

ECE559VV Project Report ECE559VV Project Report (Supplementary Notes Loc Xuan Bu I. MAX SUM-RATE SCHEDULING: THE UPLINK CASE We have seen (n the presentaton that, for downlnk (broadcast channels, the strategy maxmzng the sum-rate

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

Environmental taxation: Privatization with Different Public Firm s Objective Functions

Environmental taxation: Privatization with Different Public Firm s Objective Functions Appl. Math. Inf. Sc. 0 No. 5 657-66 (06) 657 Appled Mathematcs & Informaton Scences An Internatonal Journal http://dx.do.org/0.8576/ams/00503 Envronmental taxaton: Prvatzaton wth Dfferent Publc Frm s Objectve

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

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

Allocative Efficiency Measurement with Endogenous Prices

Allocative Efficiency Measurement with Endogenous Prices Allocatve Effcency Measurement wth Endogenous Prces Andrew L. Johnson Texas A&M Unversty John Ruggero Unversty of Dayton December 29, 200 Abstract In the nonparametrc measurement of allocatve effcency,

More information

Inexact Newton Methods for Inverse Eigenvalue Problems

Inexact Newton Methods for Inverse Eigenvalue Problems Inexact Newton Methods for Inverse Egenvalue Problems Zheng-jan Ba Abstract In ths paper, we survey some of the latest development n usng nexact Newton-lke methods for solvng nverse egenvalue problems.

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 7 GENERAL EQUILIBRIUM

PROBLEM SET 7 GENERAL EQUILIBRIUM PROBLEM SET 7 GENERAL EQUILIBRIUM Queston a Defnton: An Arrow-Debreu Compettve Equlbrum s a vector of prces {p t } and allocatons {c t, c 2 t } whch satsfes ( Gven {p t }, c t maxmzes βt ln c t subject

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

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

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

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

NON-CENTRAL 7-POINT FORMULA IN THE METHOD OF LINES FOR PARABOLIC AND BURGERS' EQUATIONS

NON-CENTRAL 7-POINT FORMULA IN THE METHOD OF LINES FOR PARABOLIC AND BURGERS' EQUATIONS IJRRAS 8 (3 September 011 www.arpapress.com/volumes/vol8issue3/ijrras_8_3_08.pdf NON-CENTRAL 7-POINT FORMULA IN THE METHOD OF LINES FOR PARABOLIC AND BURGERS' EQUATIONS H.O. Bakodah Dept. of Mathematc

More information

Psychology 282 Lecture #24 Outline Regression Diagnostics: Outliers

Psychology 282 Lecture #24 Outline Regression Diagnostics: Outliers Psychology 282 Lecture #24 Outlne Regresson Dagnostcs: Outlers In an earler lecture we studed the statstcal assumptons underlyng the regresson model, ncludng the followng ponts: Formal statement of assumptons.

More information

Global Sensitivity. Tuesday 20 th February, 2018

Global Sensitivity. Tuesday 20 th February, 2018 Global Senstvty Tuesday 2 th February, 28 ) Local Senstvty Most senstvty analyses [] are based on local estmates of senstvty, typcally by expandng the response n a Taylor seres about some specfc values

More information

Integrated approach in solving parallel machine scheduling and location (ScheLoc) problem

Integrated approach in solving parallel machine scheduling and location (ScheLoc) problem Internatonal Journal of Industral Engneerng Computatons 7 (2016) 573 584 Contents lsts avalable at GrowngScence Internatonal Journal of Industral Engneerng Computatons homepage: www.growngscence.com/ec

More information

EEL 6266 Power System Operation and Control. Chapter 3 Economic Dispatch Using Dynamic Programming

EEL 6266 Power System Operation and Control. Chapter 3 Economic Dispatch Using Dynamic Programming EEL 6266 Power System Operaton and Control Chapter 3 Economc Dspatch Usng Dynamc Programmng Pecewse Lnear Cost Functons Common practce many utltes prefer to represent ther generator cost functons as sngle-

More information

DETERMINATION OF TEMPERATURE DISTRIBUTION FOR ANNULAR FINS WITH TEMPERATURE DEPENDENT THERMAL CONDUCTIVITY BY HPM

DETERMINATION OF TEMPERATURE DISTRIBUTION FOR ANNULAR FINS WITH TEMPERATURE DEPENDENT THERMAL CONDUCTIVITY BY HPM Ganj, Z. Z., et al.: Determnaton of Temperature Dstrbuton for S111 DETERMINATION OF TEMPERATURE DISTRIBUTION FOR ANNULAR FINS WITH TEMPERATURE DEPENDENT THERMAL CONDUCTIVITY BY HPM by Davood Domr GANJI

More information

CHAPTER 5 NUMERICAL EVALUATION OF DYNAMIC RESPONSE

CHAPTER 5 NUMERICAL EVALUATION OF DYNAMIC RESPONSE CHAPTER 5 NUMERICAL EVALUATION OF DYNAMIC RESPONSE Analytcal soluton s usually not possble when exctaton vares arbtrarly wth tme or f the system s nonlnear. Such problems can be solved by numercal tmesteppng

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

This column is a continuation of our previous column

This column is a continuation of our previous column Comparson of Goodness of Ft Statstcs for Lnear Regresson, Part II The authors contnue ther dscusson of the correlaton coeffcent n developng a calbraton for quanttatve analyss. Jerome Workman Jr. and Howard

More information

Constant Best-Response Functions: Interpreting Cournot

Constant Best-Response Functions: Interpreting Cournot Internatonal Journal of Busness and Economcs, 009, Vol. 8, No., -6 Constant Best-Response Functons: Interpretng Cournot Zvan Forshner Department of Economcs, Unversty of Hafa, Israel Oz Shy * Research

More information

On the correction of the h-index for career length

On the correction of the h-index for career length 1 On the correcton of the h-ndex for career length by L. Egghe Unverstet Hasselt (UHasselt), Campus Depenbeek, Agoralaan, B-3590 Depenbeek, Belgum 1 and Unverstet Antwerpen (UA), IBW, Stadscampus, Venusstraat

More information

A PROBABILITY-DRIVEN SEARCH ALGORITHM FOR SOLVING MULTI-OBJECTIVE OPTIMIZATION PROBLEMS

A PROBABILITY-DRIVEN SEARCH ALGORITHM FOR SOLVING MULTI-OBJECTIVE OPTIMIZATION PROBLEMS HCMC Unversty of Pedagogy Thong Nguyen Huu et al. A PROBABILITY-DRIVEN SEARCH ALGORITHM FOR SOLVING MULTI-OBJECTIVE OPTIMIZATION PROBLEMS Thong Nguyen Huu and Hao Tran Van Department of mathematcs-nformaton,

More information

III. Econometric Methodology Regression Analysis

III. Econometric Methodology Regression Analysis Page Econ07 Appled Econometrcs Topc : An Overvew of Regresson Analyss (Studenmund, Chapter ) I. The Nature and Scope of Econometrcs. Lot s of defntons of econometrcs. Nobel Prze Commttee Paul Samuelson,

More information

NP-Completeness : Proofs

NP-Completeness : Proofs NP-Completeness : Proofs Proof Methods A method to show a decson problem Π NP-complete s as follows. (1) Show Π NP. (2) Choose an NP-complete problem Π. (3) Show Π Π. A method to show an optmzaton problem

More information

European Regional Science Association 36th European Congress ETH Zurich, Switzerland August 1996

European Regional Science Association 36th European Congress ETH Zurich, Switzerland August 1996 European Regonal Scence Assocaton 36th European Congress ETH Zurch, Swtzerland 6-3 August 996 Se-l Mun and Mn-xue Wang raduate School of nformaton Scences Tohoku Unversty Katahra Cho-me, Aoba-ku, Senda

More information

COMPOSITE BEAM WITH WEAK SHEAR CONNECTION SUBJECTED TO THERMAL LOAD

COMPOSITE BEAM WITH WEAK SHEAR CONNECTION SUBJECTED TO THERMAL LOAD COMPOSITE BEAM WITH WEAK SHEAR CONNECTION SUBJECTED TO THERMAL LOAD Ákos Jósef Lengyel, István Ecsed Assstant Lecturer, Professor of Mechancs, Insttute of Appled Mechancs, Unversty of Mskolc, Mskolc-Egyetemváros,

More information

Games and Market Imperfections

Games and Market Imperfections Games and Market Imperfectons Q: The mxed complementarty (MCP) framework s effectve for modelng perfect markets, but can t handle mperfect markets? A: At least part of the tme A partcular type of game/market

More information

Chapter 3 Describing Data Using Numerical Measures

Chapter 3 Describing Data Using Numerical Measures Chapter 3 Student Lecture Notes 3-1 Chapter 3 Descrbng Data Usng Numercal Measures Fall 2006 Fundamentals of Busness Statstcs 1 Chapter Goals To establsh the usefulness of summary measures of data. The

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

Supporting Materials for: Two Monetary Models with Alternating Markets

Supporting Materials for: Two Monetary Models with Alternating Markets Supportng Materals for: Two Monetary Models wth Alternatng Markets Gabrele Camera Chapman Unversty Unversty of Basel YL Chen Federal Reserve Bank of St. Lous 1 Optmal choces n the CIA model On date t,

More information

The Study of Teaching-learning-based Optimization Algorithm

The Study of Teaching-learning-based Optimization Algorithm Advanced Scence and Technology Letters Vol. (AST 06), pp.05- http://dx.do.org/0.57/astl.06. The Study of Teachng-learnng-based Optmzaton Algorthm u Sun, Yan fu, Lele Kong, Haolang Q,, Helongang Insttute

More information

Computing Correlated Equilibria in Multi-Player Games

Computing Correlated Equilibria in Multi-Player Games Computng Correlated Equlbra n Mult-Player Games Chrstos H. Papadmtrou Presented by Zhanxang Huang December 7th, 2005 1 The Author Dr. Chrstos H. Papadmtrou CS professor at UC Berkley (taught at Harvard,

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

The Minimum Universal Cost Flow in an Infeasible Flow Network

The Minimum Universal Cost Flow in an Infeasible Flow Network Journal of Scences, Islamc Republc of Iran 17(2): 175-180 (2006) Unversty of Tehran, ISSN 1016-1104 http://jscencesutacr The Mnmum Unversal Cost Flow n an Infeasble Flow Network H Saleh Fathabad * M Bagheran

More information

CS286r Assign One. Answer Key

CS286r Assign One. Answer Key CS286r Assgn One Answer Key 1 Game theory 1.1 1.1.1 Let off-equlbrum strateges also be that people contnue to play n Nash equlbrum. Devatng from any Nash equlbrum s a weakly domnated strategy. That s,

More information

The Value of Demand Postponement under Demand Uncertainty

The Value of Demand Postponement under Demand Uncertainty Recent Researches n Appled Mathematcs, Smulaton and Modellng The Value of emand Postponement under emand Uncertanty Rawee Suwandechocha Abstract Resource or capacty nvestment has a hgh mpact on the frm

More information

An (almost) unbiased estimator for the S-Gini index

An (almost) unbiased estimator for the S-Gini index An (almost unbased estmator for the S-Gn ndex Thomas Demuynck February 25, 2009 Abstract Ths note provdes an unbased estmator for the absolute S-Gn and an almost unbased estmator for the relatve S-Gn for

More information

Kernel Methods and SVMs Extension

Kernel Methods and SVMs Extension Kernel Methods and SVMs Extenson The purpose of ths document s to revew materal covered n Machne Learnng 1 Supervsed Learnng regardng support vector machnes (SVMs). Ths document also provdes a general

More information

Supporting Information for: Two Monetary Models with Alternating Markets

Supporting Information for: Two Monetary Models with Alternating Markets Supportng Informaton for: Two Monetary Models wth Alternatng Markets Gabrele Camera Chapman Unversty & Unversty of Basel YL Chen St. Lous Fed November 2015 1 Optmal choces n the CIA model On date t, gven

More information

Conjectures in Cournot Duopoly under Cost Uncertainty

Conjectures in Cournot Duopoly under Cost Uncertainty Conjectures n Cournot Duopoly under Cost Uncertanty Suyeol Ryu and Iltae Km * Ths paper presents a Cournot duopoly model based on a condton when frms are facng cost uncertanty under rsk neutralty and rsk

More information

Copyright (C) 2008 David K. Levine This document is an open textbook; you can redistribute it and/or modify it under the terms of the Creative

Copyright (C) 2008 David K. Levine This document is an open textbook; you can redistribute it and/or modify it under the terms of the Creative Copyrght (C) 008 Davd K. Levne Ths document s an open textbook; you can redstrbute t and/or modfy t under the terms of the Creatve Commons Attrbuton Lcense. Compettve Equlbrum wth Pure Exchange n traders

More information

Newton s Method for One - Dimensional Optimization - Theory

Newton s Method for One - Dimensional Optimization - Theory Numercal Methods Newton s Method for One - Dmensonal Optmzaton - Theory For more detals on ths topc Go to Clck on Keyword Clck on Newton s Method for One- Dmensonal Optmzaton You are free to Share to copy,

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

Week3, Chapter 4. Position and Displacement. Motion in Two Dimensions. Instantaneous Velocity. Average Velocity

Week3, Chapter 4. Position and Displacement. Motion in Two Dimensions. Instantaneous Velocity. Average Velocity Week3, Chapter 4 Moton n Two Dmensons Lecture Quz A partcle confned to moton along the x axs moves wth constant acceleraton from x =.0 m to x = 8.0 m durng a 1-s tme nterval. The velocty of the partcle

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

Credit Card Pricing and Impact of Adverse Selection

Credit Card Pricing and Impact of Adverse Selection Credt Card Prcng and Impact of Adverse Selecton Bo Huang and Lyn C. Thomas Unversty of Southampton Contents Background Aucton model of credt card solctaton - Errors n probablty of beng Good - Errors n

More information

Bilateral Trade Flows and Nontraded Goods

Bilateral Trade Flows and Nontraded Goods The Emprcal Economcs Letters, 7(5): (May 008) ISSN 1681 8997 Blateral Trade Flows and Nontraded Goods Yh-mng Ln Department of Appled Economcs, Natonal Chay Unversty. 580 Snmn Road, Chay, 600, Tawan Emal:

More information

Electrical double layer: revisit based on boundary conditions

Electrical double layer: revisit based on boundary conditions Electrcal double layer: revst based on boundary condtons Jong U. Km Department of Electrcal and Computer Engneerng, Texas A&M Unversty College Staton, TX 77843-318, USA Abstract The electrcal double layer

More information

Finite Element Modelling of truss/cable structures

Finite Element Modelling of truss/cable structures Pet Schreurs Endhoven Unversty of echnology Department of Mechancal Engneerng Materals echnology November 3, 214 Fnte Element Modellng of truss/cable structures 1 Fnte Element Analyss of prestressed structures

More information

University of California, Davis Date: June 22, 2009 Department of Agricultural and Resource Economics. PRELIMINARY EXAMINATION FOR THE Ph.D.

University of California, Davis Date: June 22, 2009 Department of Agricultural and Resource Economics. PRELIMINARY EXAMINATION FOR THE Ph.D. Unversty of Calforna, Davs Date: June 22, 29 Department of Agrcultural and Resource Economcs Department of Economcs Tme: 5 hours Mcroeconomcs Readng Tme: 2 mnutes PRELIMIARY EXAMIATIO FOR THE Ph.D. DEGREE

More information

VQ widely used in coding speech, image, and video

VQ widely used in coding speech, image, and video at Scalar quantzers are specal cases of vector quantzers (VQ): they are constraned to look at one sample at a tme (memoryless) VQ does not have such constrant better RD perfomance expected Source codng

More information

Numerical Solution of Ordinary Differential Equations

Numerical Solution of Ordinary Differential Equations Numercal Methods (CENG 00) CHAPTER-VI Numercal Soluton of Ordnar Dfferental Equatons 6 Introducton Dfferental equatons are equatons composed of an unknown functon and ts dervatves The followng are examples

More information

En Route Traffic Optimization to Reduce Environmental Impact

En Route Traffic Optimization to Reduce Environmental Impact En Route Traffc Optmzaton to Reduce Envronmental Impact John-Paul Clarke Assocate Professor of Aerospace Engneerng Drector of the Ar Transportaton Laboratory Georga Insttute of Technology Outlne 1. Introducton

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

Lecture 12: Classification

Lecture 12: Classification Lecture : Classfcaton g Dscrmnant functons g The optmal Bayes classfer g Quadratc classfers g Eucldean and Mahalanobs metrcs g K Nearest Neghbor Classfers Intellgent Sensor Systems Rcardo Guterrez-Osuna

More information

On the Multicriteria Integer Network Flow Problem

On the Multicriteria Integer Network Flow Problem BULGARIAN ACADEMY OF SCIENCES CYBERNETICS AND INFORMATION TECHNOLOGIES Volume 5, No 2 Sofa 2005 On the Multcrtera Integer Network Flow Problem Vassl Vasslev, Marana Nkolova, Maryana Vassleva Insttute of

More information

Question No. 1 (12 points)

Question No. 1 (12 points) Fnal Exam (3 rd Year Cvl) ransportaton lannng & rac Engneerng Date: uesday 4 June 20 otal Grade: 00 onts me: 09:30am 2:30pm Instructor: Dr. Mostaa Abo-Hashema, roessor Notes:. Answer all questons and assume

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

2 Finite difference basics

2 Finite difference basics Numersche Methoden 1, WS 11/12 B.J.P. Kaus 2 Fnte dfference bascs Consder the one- The bascs of the fnte dfference method are best understood wth an example. dmensonal transent heat conducton equaton T

More information

Orientation Model of Elite Education and Mass Education

Orientation Model of Elite Education and Mass Education Proceedngs of the 8th Internatonal Conference on Innovaton & Management 723 Orentaton Model of Elte Educaton and Mass Educaton Ye Peng Huanggang Normal Unversty, Huanggang, P.R.Chna, 438 (E-mal: yepeng@hgnc.edu.cn)

More information

LOW BIAS INTEGRATED PATH ESTIMATORS. James M. Calvin

LOW BIAS INTEGRATED PATH ESTIMATORS. James M. Calvin Proceedngs of the 007 Wnter Smulaton Conference S G Henderson, B Bller, M-H Hseh, J Shortle, J D Tew, and R R Barton, eds LOW BIAS INTEGRATED PATH ESTIMATORS James M Calvn Department of Computer Scence

More information