and close, shedding large numbers<sup>of jobs; if employment in the affected sector</sup> dominates the local economy<sup>then this canhave large negativeexternalitieson other</sup> businesses. Enterprises in the<sup>sectors gainingfrom reformsmay be locatedin different</sup> places and draw upon a different<sup>pool of labour.Thus althoughthe nationalaggregateof</sup> employment may be little affected<sup>by reforms,localeffectscan be considerableand</sup> longer lasting.

The opposite extreme from assuming<sup>a zerowageelasticityof labouris toassumethat it</sup> is infinitely elastic implying that,<sup>if a sector expands,employmenttends torise rather than</sup> wages. In some sectors and countries<sup>this may be nearer the truth than assuminga zero</sup> elasticity (the empirical evidence<sup>is mixed -see thesurvey by Matusz and Tarr (1999);</sup> Winters (2002) presents evidence<sup>that employmentadjustedmore than wagesin India</sup> during the 1990s). In practical<sup>termsit may besensible totake intoaccount the</sup> segmented nature of many<sup>labour marketsin developingcountries,since the simplest</sup> assumption of an infinitely<sup>elastic labour supply suggestssomewhat unrealisticallythat</sup> the "wage" when out of work<sup>is exactly the sameas thewage inemployment.It may be</sup> better to assume that employment<sup>expandsin the gaining sectorsat the existingsector or</sup> location specific wage.'<sup>6</sup> If we assume that employment<sup>expandsat a fixedsectorspecificwage and wish to</sup> simulate the impact of an increase<sup>indemand then we needa way of moving peopleinto</sup> and out ofjobs. It is clearly<sup>rather unrealisticto suppose that all of these new jobs willbe</sup> filled from the ranks of the previously<sup>unemployed;in many casespeople willswitch</sup> from one job to another in<sup>order totakeadvantageof thedifferencesin sectoralwage</sup> rates. Nicita et al (2002) provide<sup>a useful approach to calculating who is likely togain</sup> from an expansion in employment.<sup>They calculatethe probability of being in different</sup> forms of employment using<sup>a multinomiallogit, rank householdsaccordingto these</sup> probabilities and then put them<sup>into jobs in theorder of their probability.Thisapproach</sup> fits nicely with the intuition<sup>that, when formalsectorsgrowit is often not the poor who</sup> get the jobs, or at least not<sup>at first. In addition,if thenew wage "allocated"toa</sup> household on getting a job is<sup>determined by a wage equation which takes intoaccount</sup> sectoral wage differentials<sup>then it will be possiblefor there to be discrete changesin</sup> income when a person gets a job.

This approach has been applied<sup>in the IntegratedFrameworkstudiesfor a number of</sup> different countries. For example,<sup>the study for the Republic of Yemen(2002)simulates</sup> the impact of a 6 percent increase<sup>in female participationinthe labour market.Since</sup> poorer households are more<sup>likely to participatein the labour market in Yemen, two-</sup> thirds of the households affected<sup>by the increase in employment opportunitiesare in the</sup> bottom three expenditure deciles.<sup>Furthermore,the averageimpactfor those households</sup> that have a new entrant to the<sup>labourforce is equivalentto 30 percent of total household</sup> expenditures. Similarly in<sup>Malawi,Ajwad,Aksoyand Sivri (2002) simulate the poverty</sup> impact of a 30% increase in<sup>employmentin manufacturing, constructionandmining.</sup> 16 Or at least that the formal sector<sup>wageis higherthan the subsistencewage.</sup> 15