FORGONE EARNINGS FROM SMOKING: EVIDENCE FOR A DEVELOPING COUNTRY

Transcription

1 FORGONE EARNINGS FROM SMOKING: EVIDENCE FOR A DEVELOPING COUNTRY Mchael Lokshn and Kathleen Beegle * Development Research Group, World Bank ABSTRACT Ths paper estmates the economc losses related to the negatve effect of smokng on wages n a context of a developng country. Usng data from 2005 Albana Lvng Standards Montorng Survey, we jontly estmate a system of three equatons: the smokng decson and two separate wage equatons for smokers and non-smokers. The results show that, after controllng for observed characterstcs and takng nto account unobserved heterogenety n personal characterstcs, smokng has a substantal negatve mpact on wages. On average smokers wages are 20 percent lower than the wages of smlar non-smokers, provdng strong evdence for the potental polcy relevance of tobacco control ntatves for developng countres. September 4, 2006 * The fndngs and nterpretaton of ths paper are those of the authors and should not be attrbuted to the World Bank Group, ts Executve Drectors, or the countres they represent. Address for correspondence: Mchael M. Lokshn, e-mal: mlokshn@worldbank.org; Kathleen Beegle, e-mal: kbeegle@worldbank.org, phone Both at Development Economcs Research Group, The World Bank, 88 H Street NW, Washngton, DC 20433, We thank Martn Ravallon, Jed Fredman, Jshnu Das, and Gero Carletto for useful and constructve comments.

2 . Introducton In 2000, about one out of three adults, or. to.2 bllon people worldwde, smoked (WHO 999). By 200 the number of smokers s expected to grow to around.3 bllon (FAO 2003). The vast majorty of the world s smokers (82 percent) lve n developng countres where, n sharp contrast to developed countres, the consumpton of tobacco s on the rse. Tobacco control s ncreasngly seen as a publc health prorty, motvatng campagns such as the World Health Organzaton s Tobacco Free Intatve as well as country-specfc tobacco control campagns. These efforts are justfed not only on grounds related to well-establshed adverse effects of smokng on health, but more generally on economc grounds. The gross healthcare cost of smokng for the developng countres s estmated to be as hgh as. percent of GDP (Jha and Chaloupka 2000). The economc costs assocated wth losses n productvty because of smokng could be at least as large and be dsproportonately ncurred by the poor (The World Bank 999). Estmates of the economc costs of smokng tend to reflect costs assocated wth ncreased premature death and health-care costs related to smokng-nduced chronc dseases (whch can affect smokers as well as non-smokers exposed to smoke). In addton to these pathways, there s a thrd category of costs that has been consdered: the earnngs and wage reductons assocated wth smokng. The lterature on the relatonshp between smokng and labor market performance s very lmted and based on data from Western Europe and the US. Berger and Legh (989) examne the effect of smokng and beng overweght on earnngs usng the 973 Qualty of Employment survey n the US. Ther study fnds no statstcally sgnfcant assocaton between smokng and earnngs for male and female workers. Levne et al. (997) nvestgate the effect of smokng on wages usng panel data from US. They compare wages of contnuous smokers wth the wages of workers who qut smokng. Controllng for observable and tme-nvarant unobservable characterstcs, smokng s estmated to lower a worker s wage by about 4 8 percent. Drawng on data from Germany, Heneck and Schwarze (2003) examne whether smokng affects earnngs of employees 25 to 55 years old. Dependng on the The WHO estmates that tobacco s the second major cause of death worldwde and the fourth most common rsk factor for dsease worldwde. 2

3 model specfcaton, the estmated losses n earnngs for smokers range from 2 to 8 percent compared to non-smokers. Several studes examne the smultaneous effect of alcohol and smokng on earnngs. Van Ours (2002) focuses on the smultaneous wage effects of alcohol and tobacco usng the sample of respondents 6 years and older n Netherlands. Controllng for unobserved heterogenety and endogenety of drnkng and smokng, the study estmates that the wages of smokers are 0 percent lower than the wages of otherwse dentcal non-smokers. Auld (2005) estmates the model of drnkng, smokng and wages usng the sample of employed Canadan men. After accountng for endogenous nature of the decson to use alcohol and tobacco and ther smultaneous effects on wages, he fnds that daly smokers have wages about 30 percent lower than non-smokers. The lmted set of studes of the wage or earnngs consequences of smokng consstently show sgnfcant negatve effects. However, these results are restrcted to hgh-ncome settngs; estmates of the economc costs of smokng n developng countres are non-exstent to our knowledge. Ths paper addresses ths gap n the lterature by estmatng the economc losses related to the negatve effect of smokng on wages n a developng country, namely Albana, where 60 percent of adult males and 8 percent of females smoked n 2002 and the number of smokers has been ncreasng rapdly over the last decade (WHO 2002). Ant-smokng polces are hgh on the country agenda. In January 2006 the Government of Albana submtted a new draft law on tobacco and smokng that outlaw sales of cgarettes to mnors younger than 8, and present strcter rules for tobacco ndustry regardng sale and advertsng of tobacco products (ENSP 2006). Usng recent household survey data, we estmate a system of three equatons: the smokng decson (never havng smoked and current smokers) and two separate wage equatons, one for smokers and one for non-smokers. By jontly estmatng ths system by Full Informaton Maxmum Lkelhood we control for the effects of observed and unobserved characterstcs that may be correlated wth wages and smokng status. Moreover, we ntroduce new and arguably mproved nstrumental varables to dentfy the causal effect of the smokng decson on wages. The results show that, after controllng for observed characterstcs and takng nto account unobserved heterogenety 3

4 n personal characterstcs, smokng has a substantal negatve mpact on wages. On average smokers wages are 20 percent lower than the wages of smlar nonsmokers, provdng strong evdence for the potental polcy relevance of tobacco control ntatves for developng countres. The structure of the paper s as follows: the methodology and emprcal approach are dscussed n Secton 2. The data are dscussed n Secton 3. Secton 4 presents the emprcal results and conclusons are drawn n the last secton. 2. Methodology and emprcal specfcaton Several theores have been proposed to explan the lower wages assocated wth smokng. Health effects of smokng are arguably the most frequently noted lnk; smokng causes varous morbdtes, whch make smokers less healthy and could therefore result n lower labor productvty. A second, partally health-related channel, s the hgher costs to employers of hrng a smoker relatve to a non-smoker (for example, due to healthcare costs nduced by smokng). Even f smokers are equally productve or do not ncur more costs n employment, dscrmnaton aganst smokers n the workplace may result n lower earnngs for those who smoke. Fnally, smokng could be correlated wth lower earnngs because of the dfferences n preferences over present and future consumpton between smokers and non-smokers. We dscuss each of these theores n turn. The adverse health mplcatons of smokng could affect a worker s productvty and, therefore, labor market outcomes. Levne et al. (997) report that smokng s assocated wth lower physcal endurance even for the young workers. Young smokers are also more lkely to experence respratory nfectons (Conway and Cronan 992; Hoad and Clay 992). The negatve effects of smokng accumulate wth age and the productvty consequences of smokng could be larger for older workers. The hgher ncdence of respratory dseases among young smokers and more serous llnesses at older ages can result n lower productvty and hgher absenteesm (Bertera 99). Net of productvty effects, employers face hgher costs to hre a smoker. The cost of medcal nsurance for smokers s hgher (Bertera 99). In turn, larger health nsurance clams would reflect negatvely on wages of smokers, as employers are unwllng to pay 4

5 for all or part of the hgher costs of employng smokers. At the same tme, workers who are aware of the negatve consequences of smokng mght select themselves nto occupatons that provde better health coverage, acceptng lower wages n exchange. The cost of the smokng worker for hs employer could also rse gven the need for addtonal facltes for smokers that would ncrease ar coolng, heatng, and ventlaton cost, ncreased fre hazard and fre nsurance premums, and smoke polluton leadng to larger cleanng and mantenance costs (CHPP 2000). Dscrmnaton aganst smokers s another potental reason for observed dfferences n wages between smokers and non-smokers. Employers mght dscrmnate aganst smokng employees because of the possble effect of second-hand smokng on the other employees and on the customers. Statstcal dscrmnaton may also exsts f employers assume that an ndvdual smoker s less productve based on the average health effects of smokng 2. These three theores lnkng smokng to wage outcomes propose that smokers, all thngs equal, wll realze lower wages. A fourth theoretcal consderaton would be that smokng s a proxy for some other personal characterstcs that could affect wages. For example, ndvduals wth hgher valuaton of present versus future consumpton may be more lkely to smoke and less lkely to nvest n productvty-enhancng human captal. Ths theory centers on the observaton that the costs of smokng are related to the negatve effects of smokng on health whch often are realzed only n the longer-term. On the other hand, the perceved benefts of smokng are predomnantly mmedately realzed and mght nclude stmulaton, enhancement of concentraton and short-term memory, and, to a certan degree, wegh control (Rohsenow et al. 2003). Smokers expect desrable and postve effects of smokng n terms of facltatng of socal nteractons and relaxaton (Brandon and Baker 99). Mood-alterng ablty of ncotne tends to allevate boredom and reduce stress as well as aggressve responses to stressful events (Senagore 2006). So, ndvduals who smoke are choosng the short-run benefts over the long-run costs, thereby perhaps revealng a hgher rate of tme preference than non-smokers. Fuchs 2 Dscrmnaton may be much more relevant n the US context where socal norms make smokng less acceptable as reflected n state-level bans aganst smokng n publc spaces compared to Albana where there are no restrctons aganst smokng. Heneck and Schwarze (2003) make the pont that n Germany dscrmnaton aganst smokers s more moderate than n the US; arguably one could make smlar case for Albana where smokng prevalence s even hgher. 5

6 (982) suggests that smokng s therefore an ndcaton or proxy of a hgh rate of tme preference resultng n lower human captal accumulaton and lower earnngs, as evdenced by Evans and Montgomery (994) and Lahr and Song (2000). Lkewse smokers may have flatter earnng profles f they have a hgher rate of tme preference. In the Ratonal Addcton Theory (Becker and Murphy 988) a decson to smoke s based on comparson of the present and future costs and benefts of smokng (Chaloupka 99, Becker et al. 994). Gven these theores that lnk smokng to wages, one emprcal approach would be to estmate a wage equaton based on a model of wage determnaton that relates wages wth the ndvdual human captal characterstcs (Mncer 974) modfed to nclude smokng. In the smplest case the wage functon has a form: ln W = X β + S γ + ε () where W represents monthly wages of an ndvdual, X s a vector of exogenous ndvdual characterstcs, S s dummy varable of the ndvdual smokng status, and ε s an..d., mean-zero error term, and β s a vector of parameters. In ths specfcaton, parameter γ could be nterpreted as an effect of smokng on wages. Whle the dfference n observable characterstcs of smokers and non-smokers could be controlled for by a standard regresson approach, the presence of unobservable factors affectng both smokng and earnngs would lead to the endogenety of S n (). As a result of such endogenety the estmaton of the effect of smokng on wages would be based. 3 For example, ndvduals who choose to smoke may be dfferent from nonsmokers n some unobserved dmensons that are negatvely (postvely) correlated wth wages. As noted above, rate of tme preference s one possble trat that s unobserved to the analyst and ts omsson bases estmates n equaton (). The challenge for the emprcal strategy s to estmate the effect of smokng on wages controllng for such unobserved factors. We use two alternatve methods to address ths: a standard two-stage 3 The reverse causalty of the effect of wages on smokng s partly mtgated by the evdence of the addctve nature of smokng that could be especally strong n the developng countres. Lance et al. (2004) report a prce-elastcty of cgarette consumpton for Chna and Russa to be n the range of 0 to -0.5, estmates whch are much lower than the estmates of the elastcty n the US (0.40). The authors note that ths low elastcty demonstrates the strong addcton of consumers to cgarettes. Developng countres often lack the defned regulatons on producton of cgarettes. As a result, cgarettes are lkely to have hgher ncotne content and to be more addctve on average than n the developed countres. 6

7 least square nstrumental varables (2SLS) regresson and the swtchng regresson approach (e.g., Lee 978). The 2SLS model s appealng for at least two reasons. Frst, the prevous studes noted above use 2SLS to estmate the effect of addctve behavor on wages. Second, 2SLS produces an easly-nterpreted measure of the effect of smokng: γ. On the other hand, ths specfcaton assumes that the effect of personal characterstcs on wages s lnear and ndependent of smokng status. Ths assumpton can be relaxed by allowng a complete nteracton of a varable for the smokng status and exogenous varables n the wage equaton. 4 The smultaneous estmaton of the resultng two wage equaton, one for smokers and another for non-smokers, and the equaton for the smokng status represents the swtchng regresson model formally expressed as: S * lnw lnw = Z η + u 2 = X β + ε = X 2 2 β + ε 2 observed observed f f S S * * 0 ( smokes) < 0 ( does not smoke) (2) where * S s a latent propensty to smoke, Z s a vector of exogenous characterstcs, u, ε, and ε 2 are the normally dstrbuted error terms, η s vector of parameters, and superscrpt dentfes smokers and 2 dentfes non-smokers. The dentfcaton condtons n (2) are that dsturbance terms u and ε s are ndependent, or else there s at least one varable n Z that s not ncluded n X. Assumng that (X, ε, ε 2, and u) are..d., and ε, ε 2 and u have, condtonal on X, a jont normal dstrbuton wth mean zero and postve defnte covarance matrx, the system of equatons (2) could be estmated by Full Informaton Maxmum Lkelhood method (FIML). The dentfcaton restrctons for the 2SLS estmaton are smlar. Several studes use nstrumental varable approach for dentfyng the effect of smokng and alcohol consumpton and smokng on wages. Lye and Hrschberg (2000) appled the two-step Heckman (979) correcton approach to control for endogenety of smokng and alcohol consumpton. The paper does not explctly dscuss the 4 We can also consder the ntermedate model that s a FIML estmaton of the effect of an endogenous bnary varable on another endogenous contnuous varable, condtonal on two sets of ndependent varables the so-called treatment effect regresson model (e.g., Maddala 983). That model s more restrctve n comparson wth the FIML swtchng regresson model and brngs no new nsghts nto our analyss. The results of treatment effect regresson are avalable from the authors on request. 7

8 dentfcaton condtons, but seems to rely on dentfcaton by the functonal form. Such an approach could be problematc due to the weak nstruments bas (Stager and Stock 997). The nstrumental varables n Van Ours (2002) nclude whether the respondent has a partner and whether the respondent ndcated the early start of smokng. Auld (2005) ncludes relgon and the prce of tobacco as nstrumental varables. Heneck and Schwarze (2003) use such varables as strong relgous convcton and martal status as nstruments n ther 2SLS estmaton. In our vew, t s hard to justfy the valdty of these nstruments for dentfcaton of the effect of smokng on wages. Emprcal research has consstently shown that marred men have substantally hgher wages, on average, than otherwse smlar unmarred men, the so-called marrage wage premum phenomenon (e.g., Cornwell and Rupert 997, Danel 99, Gray 997). Early start of smokng may be an nvald nstrument f length of smokng exposure drectly affects wages through health; long-term adverse effects of teenage smokng on health are well-documented n the medcal lterature (e.g. CDC 994). Usng the prce of tobacco as an nstrument could also be problematc because of the addctve nature of smokng (see footnote 3). Fnally, t s dffcult to argue that relgous belefs, whle affectng the ndvdual s probablty to smoke, have no effect on earnngs gven the extensve lterature that demonstrates the opposte (e.g., Ngel 984). Indeed, Van Ours (2002) concludes that t s dffcult to fnd good nstrumental varables and Heneck and Schwarze (2003) state that ther dentfyng nstruments perform poor[ly] n the frst stage of 2SLS regresson. 5 Our dentfcaton strategy reles on two varables about smokng behavor of the respondent s parents. We had an opportunty to ntroduce these varables n the ALSMS questonnare specfcally for the purpose of usng them as nstruments n the current analyss. We argue that the parental smokng hstory s correlated wth the probablty to smoke and has no drect mpact on ndvdual s earnngs 6. The effect of parental smokng on offsprng tobacco use s well establshed n the lterature (e.g., Andrews et al. 993; Pedersen and Lavk 99). Smokng parents may present a model of smokng behavor to 5 See Van Hours (2002), page ; Heneck and Schwarze (2003), page 8. 6 MacDonald and Shelds (200) use smlar nstruments n the analyss of the mpact of alcohol use on occupatonal attanments n England. Here we dscuss these nstruments n the context of probablty of beng a current smoker wth the caveat that these nstruments are arguably stronger for dentfcaton of non-smokers who never havng smoked as opposed to non-smokers who had prevously smoked and qut. 8

9 ther chldren, who are therefore at ncreased rsk of tobacco use when adults (Fagan et al. 2005). Perhaps the strongest theoretcal argument aganst the valdty of our nstruments s the adverse health effect of secondhand smokng that could affect the future productvty of chldren of smokng parents. Whle there exsts an extensve lterature on the short-term effects of secondhand smokng on health we are unaware of any study that demonstrates the drect negatve mpact of the secondhand smokng when a chld on the chld s labor productvty n adulthood. One could also argue that smokng s an ndcaton of certan personal trats of a parent, potentally unrelated to smokng, that could affect outcomes of her chldren (e.g., schoolng attanment, motvaton, etc.), whch, n turn, affect the chldren s future earnngs 7. For example, a rate of tme preference mght be transferred from parents to ther chldren genetcally or acqured n early chldhood. Then the observed low wages of the smokers relatve to non-smokers could be caused not by the smokng drectly but by the hgher rate of personal tme preferences of smokers that was somehow acqured from the parents. Omttng these measures n the estmaton could potentally nvaldate our nstruments. We partally address ths by ncludng educaton of parents n our emprcal specfcaton the only addtonal parental nformaton that s avalable n the data. The rates of tme preferences of the parents would be reflected n ther educatonal achevements, thus clearng our nstruments from the component potentally correlated wth respondents wages. The educatonal achevements of the parents are qute smlar between the groups of smokers and those who never smoked, ndrectly lendng support to our chosen nstrument. Nevertheless, gven the lmtatons of our data, we can never be sure that our nstruments capture no unobserved characterstcs of the parents that could be correlated wth the respondents labor market outcomes. Thus, our estmates could reflect not only the drect effect of smokng on wages but also the effects of these unobservables. The effect of smokng on wages s estmated dfferently n our two emprcal models. The coeffcent on the endogenous dummy varable S n the 2SLS regresson 7 We know of no study confrmng that mult-level effect of parental smokng on chldren s future earnngs. In addton, we would thnk that the nfluence of these factors on the future productvty would be less pronounced n Albana, where more than 60 percent of respondents grew up wth smokng parents. 9

10 estmates the effect drectly. In the FIML model the effect could be derved by comparng the predcted expected wages of smokers wth the expected wages they would receve had they been non-smokers or qutters (the counterfactual wage). The expected wage of a smoker could be expressed as: ϕ( ηz ) E(ln w X, S = ) = βx + ρσ = βx + ( Z S = ) βλ λ (3.) Φ( ηz ) Smlarly, the expected wage of non-smoker s expressed as: ϕ( ηz ) 2 2 E(ln w2 X, S = 0) = β2 X + ρ2σ 2 = β2 X + 2 ( Z S = 0) 2 βλ λ (3.2) Φ( ηz ) 2 2 where and σ and σ 2 are varances of the error terms n the wage equatons, and ρ and ρ 2 are the coeffcents of correlaton between ε, ε 2 and u, and λ s are the so-called Mlls ratos. From (3.-2) the expected counterfactual wage for the sub-sample of smokers s: E(ln w X, S = 0) = β 2X + ρ2σ 2λ( Z S = ) (4) The nterpretaton of our results depends on how we model our counterfactual. There s no consensus on the choce of the comparson group n the lterature on smokng and wages. The majorty of the lterature compares wages of current smokers wth everybody else (Lye and Hrschberg 2004, Van Ours 2002, Heneck and Schwarze 2003). Levne et al. (997) compares wages of smokers only wth those who qut smokng. The man goal of our study s to evaluate the component of the economc cost of smokng related to the effect of smokng on wages. We defne the economc cost of smokng as measured by the hgher wages of smokers had they never started smokng n whch case the counterfactual of smokers s the group of those who have never smoked. There are, of course, alternatve counterfactuals that could be framed. The most obvous alternatve would be to evaluate the economc cost of contnued smokng as measured by the ncreased wages for smokers f they qut. In ths case the counterfactual of smokers s the group of qutters. However, we faled to fnd n our data convncng nstruments to dentfy the decson to qut or contnue smokng. One could also assess the changes n wages assocated wth never-smokers who begn to smoke. These alternatve counterfactuals reflect future benefts of successful ant-smokng campagns, 0

11 whereas our chosen counterfactuals measure the costs of smokng n terms of current losses n productvty. 3. Data and descrptve statstcs The data for our analyss comes from the fourth round of Albana Lvng Standard Montorng Survey (ALSMS) conducted n Aprl-July 2005 by the Albanan Insttute of Statstcs wth the techncal support of the World Bank. The ALSMS uses a two-stage stratfed clustered sample of 3640 households, and s representatve at the natonal, urban, rural, and regonal levels. 8 The ALSMS collects nformaton on the demographc characterstcs of the household members, ther labor market actvtes, educaton, heath characterstcs, and the household s access to socal servces. The questonnare also gathers nformaton on ndvdual and household ncome and consumpton expendtures as well as on ownershp of assets. A specal secton of ALSMS collects nformaton about ndvdual smokng behavor ncludng: whether the respondent smokes on a daly bass or s an ex-smoker, age at whch the respondent started smokng, number of cgarettes smoked per day, and whether the respondent s farther and mother ever smoked. For the purpose of the current analyss we restrct our sample to employed prmeage adults 25 to 60 years of age. By the age of 25 most of the adults n Albana have completed ther educaton and are actvely nvolved n the labor market. An ndvdual s consdered to be employed f he had worked n a permanent job n the week precedng the survey or was temporary absent from hs permanent job due to vacaton or llness. Our sample excludes employers, self-employed and ndvduals workng n a household farm because the wage data s not reported for ths group of respondents. The ndvdual wages were measured as net monthly payments or earnngs and bonuses. Forty percent of males and about 5 percent of females age 25 to 60 reported to have ever smoked; 32 percent of males and less than 4 percent of females n our sample have categorzed themselves as current smokers. 9 These numbers are comparable wth 8 For further nformaton on survey desgn and sample frame see: 9 That low proporton of smokng women may not reflect the actual prevalence of female smokng, as n Albana women are reluctant to admt they smoke because smokng s not seen as beng socally desrable or acceptable for females (IMF 2006).

12 other studes of smokng n Albana. The results of the Populaton-based Survey show that 38 percent of adult males and 8 percent of females were current smokers n the captal Trana n 2002 (Shapo et al. 2003). IMF (2006) reports that, accordng to 2002 LSMS survey, 3 percent of Albanan men smoked. Because of a small proporton of female smokers n the sample our further analyss wll focus only on workng males years of age. The ncdence of smokng s smlar among urban and rural male populaton n Albana. The prevalence of current smokers s close to 50 percent among the leasteducated males and declnes for better-educated men. Only one quarter of men wth a unversty degree smoke. The propensty to smoke vares for men by relgon. The hghest proporton of smokers (36 percent) s among Albanan Muslms, ncludng Bektash. Albanan Chrstans smoke at a rate of about 30 percent. The left panel of Fgure graphs the results of non-parametrc regresson (runnng-lne least-squares) for the proporton of smokers by age. The ncdence of smokng s ncreasng wth age of the respondents. Less than 20 percent of 25 years-old men classfed themselves as current smokers. The proporton of smokers ncreases sharply for older age groups peakng at about 35 percent for men 38 years old and older. The rght panel of Fgure shows the relaton between monthly log-wages and age for smokers and non-smokers. On average, non-smokers earned about 26,300 Lek (3.27 n logs) per months relatve to 24,290 Lek per month (3.9 n logs) for smokers (8.3 percent dfference). Both groups have an nverted U-shaped age-wage profle. Wages of younger males are ncreasng and reach maxmum at age of 35 and then declne for the older workers. Wages of non-smokers are hgher than wages of smokers for all age groups wth the largest gap n wages observed for workers 35 to 50 years of age. 4. Results In order to estmate the effect of smokng and the counterfactual as descrbed n Secton 3, the dependent varables n the regresson estmates are the logs of monthly wages for smokers and those who never smoked, and the bnary ndcator capturng whether a respondent s a current smoker or has never smoked. Table shows the descrptve 2

13 statstcs for the dependent and explanatory varables separately for smokers, qutters, and non-smokers. The explanatory varables n our emprcal specfcaton are classfed nto several groups. The frst group ncludes human captal characterstcs: age (squared and cubed), educatonal level, foregn languages spoken, and relgous afflaton. The second group of varables conssts of soco-demographc characterstcs of the household. These nclude the household sze and household composton varables. Condtons on the local labor markets are captured by the set of 36 dstrct dummes and the dummy for the type of localty (urban or rural). We nclude parental educaton as an ndcator of famlal background that could affect labor market motvaton or productvty whch could otherwse confound nterpretaton of smokng status n the 2SLS and FIML estmatons. Fnally, we nclude total hours worked last month. Table 2 presents the results of the estmaton of the OLS and 2SLS regresson models of the effect of smokng on wages. Accordng to the OLS regresson, smokng decreases male wages by 4.7 percent (standard error of 0.025); ths result s comparable to what was shown n Fgure. Gven concerns that smokng does not randomly occur among men n Albana, we now turn to the results on the probablty of smokng. The probablty of smokng s postvely and sgnfcantly related to whether the father of the respondent smoked; the coeffcents on mother s and father s smokng are jontly sgnfcant. Older ndvdual are more lkely to smoke relatve to the younger respondents. Prevalence of smokng s sgnfcantly lower among Catholc and sgnfcantly hgher among athests relatve to men of other relgons. Men wth the less than four years of prmary educaton are more lkely to smoke compared to bettereducated men. Estmaton also reveals some regonal dfferences of the ncdence of smokng among workng men. The key result from the frst-stage of the 2SLS regresson s the jont sgnfcance of the nstrumental varables for smokng. The Sargan s (958) test of over-dentfyng restrctons fals to reject the null hypothess that our excluded nstruments, varables on the mother s and father s smokng status, are uncorrelated wth the error term and are correctly excluded from the wage equaton. Turnng to the results of the second stage of the 2SLS estmaton, the wage reducton assocated wth smokng s much larger when smokng s treated as an 3

14 endogenous varable. We now fnd that the sze of the wage loss for smokers s equal to a 23.4 percent wage reducton (bootstrapped standard error of 9.8) compared to wages of non-smokers. 0 Ths large estmated loss n wages s comparable wth the estmates by Auld (2005) who fnds a 30 percent earnng loss for smokers n Netherlands and s hgher than the effects found n studes of smokng n the US and Canada. The results show a postve selecton bas nto smokng as found n other studes (such as Auld, 2005, and Van Ours 2002) ; OLS results underestmate the negatve wage effect of smokng. The results of the FIML estmaton of the swtchng regresson model (2) are shown on Table 3. 2 The Log-lkelhood test of ndependence s rejected n favor of jont dependence of the error terms n system (2). Hausman over-dentfcaton test (Hausman 983) confrms the valdty of our nstruments wth 5 percent sgnfcance level. Turnng to the estmatons of the earnng functons, controllng for other personal characterstcs respondent s age has a negatve and sgnfcant effect on ndvdual earnng. Marred non-smokng males earn sgnfcantly more than sngle nonsmokers and whereas martal status of smokers has no effect on ther earnngs. The relatonshp between wages and educaton of non-smokers s stronger (.e. wage-educaton profle s steeper) than for smokers. An ablty to speak Englsh s assocated wth a sgnfcant wage premum for both groups. Knowledge of Italan and Greek, on the other hand, s benefcal n term of hgher wages only for non-smokers. Overall we fnd a stronger dependence between wages and productve human captal characterstcs for non-smokers than for smokers. That could support the hypothess about the dfferences n the dscount rates of the future between smokng and non-smokng ndvduals (Evans and Montgomery 994). We evaluate the effect of smokng on wages by smulatons based on estmates n Table 3 of the parameters of equatons (4) and (5). For every smokng respondent we 0 We use smulated effects nstead of approxmate effects gven by the coeffcent on the smoker dummy n Table 2. Levne et al. (997) show mxed results n regards to evdence of the postve selecton but fnd no evdence of negatve selecton. 2 The estmaton of the swtchng regresson model and smulaton are based on the FIML algorthm mplemented as a Stata program movestay (Lokshn and Sajaa 2004). We also tred to estmate the smultaneous model wth three wage equatons for smokers, qutters, and those who never smoked by FIML. Asde from the ssue of fndng vald nstruments for dentfcaton, the model faled to converge, most lkely due to the small number of qutter n our sample. 4

15 predct hs expected wage condtonal on hm beng a smoker and compare t wth a predcted wage condtonal on not smokng. Accordng to the results of the swtchng regresson FIML, an average smoker experences a 22.5 percent reducton n hs wages (bootstrap standard error of 9.2) due to smokng. The results are not statstcally dfferent than the wage reducton assocated wth smokng produced from the 2SLS estmates. Moreover, the effect of smokng on ndvdual wages s smlar across dfferent age groups and for respondents resdng n rural and urban locatons. Yet, we do fnd evdence that the smokng penalty s lower for men wth hgher educaton: wages of smokers wth a unversty dploma are 7 percent than ther non-smokng counterparts. Several alternatve econometrc specfcatons for model (2) can be tested. In the specfcaton for Table 3 the non-smokers nclude only men who never smoked. We reestmate our model on the sample that ncludes both the respondents who never smoked and those who qut smokng (results shown n Tables A and A2 n Appendx). The effect of smokng on wages derved from ths unrestrcted sample estmaton s not dfferent than the results n Table 3; the wage loss from smokng s 27.4 percent (standard error of 9.4). We also estmate the swtchng regresson model wth the specfcaton that ncludes the occupatonal dummes (not presented). These varables could be endogenous n the wage equaton and so the results of ths estmaton should be nterpreted wth cauton. Agan, the results are largely unchanged; after controllng on occupatonal choce, an average smoker earns 26.3 percent less than a non-smoker 3. In sum, these dfferent specfcatons produce comparable (and statstcally smlar) estmates of the economc cost of smokng. Tryng to test varous hypotheses about the effect of smokng on wages we estmate three wage regressons for smokers and qutters that nclude the ntensty of smokng, expressed n cgarettes per day (only for the current smokers), and smokng experence as total years of smokng (Table 4). We fnd that wthn the group of current smokers and the respondents who qutted smokng the effect of ntensty of smokng and smokng experence s small and statstcally nsgnfcant. If ndeed employers dscrmnate aganst smokers we would expect to fnd a stronger negatve effect of the 3 The results of these estmatons are avalable from the authors on request. 5

16 ntensty of smokng on smoker s wages. To account for a potental endogenety of a smokng experence wth respect to wages, we nstrument ths varable wth the nstruments we use n our FIML estmatons. The ratonal for the nstruments s smlar: we argue that parental smokng mght affect the ntensty of smokng and age at whch an ndvdual starts smokng but has no drect effect on ndvdual wages. The results of ths IV regresson (avalable from the authors on the request) are smlar to the results of OLS estmaton,.e., the effect of smokng experence on wages of current smokers and qutters s nsgnfcant. The economc cost of smokng s large for an ndvdual smoker and the mpled socetal cost of smokng could also be substantal. Takng a conservatve estmate of the negatve effect of smokng on wages for the prme-age males to be about 20 percent and calculatng an aggregated loss n wages of 30 percent (about 400,000 workers) of current male smokers, every month the Albanan economy looses approxmately 2.6 percent of ts GDP because of negatve consequences of smokng among the prme age males Conclusons For workng prme-age men n Albana, our analyss shows that wages of smokers are sgnfcantly lower than wages of ndvduals who never smoked. The smple comparson ndcates an 8 percent wage advantage of non-smokers relatve to smokers. However, smokers dffer from non-smokers n both observable and unobservable characterstcs. Consstent wth other studes for developed countres, the wage penalty dffers dependng on how observed and unobserved trats of smokers and non-smokers are addressed. Controllng for the dfferences n observable characterstcs n an OLS regresson, the negatve wage effect of smokng perssts but s reduced to 4 percent. Takng nto account both the dfferences n observable and unobservable characterstcs of smokers and nonsmokers, the wage penalty for smokng s statstcally and economcally large: smokers experence wage reductons of 2-28 percent. The large wage reducton caused by smokng s robust to several specfcatons, ncludng 2SLS and FIML estmatons and 4 Ths smulaton s based on fgures from CIA (2006). Accordng the offcal exchange rate the 2005 GDP n Albana was $8.52 B, the total populaton was 3,500,000 people, and the average monthly wage of nonsmokers s about $230. 6

17 controls for occupaton and ntensty of smokng. Whle better-educated smokers have a slghtly lower wage penalty, there are otherwse no dfferences by other characterstcs (age and locaton). Due to data lmtatons, we can not emprcally assess to what extent each of the competng hypotheses contrbutes to the large wage reducton from smokng, although, the lack of an age-gradent n the wage penalty suggests that tme preferences can not fully explan the wage reducton. These results suggest that there are large economc costs of smokng n lowncome settngs. Some caveats to ths analyss should be mentoned. Frst, we restrct our sample to employed males. Employment s lkely to be endogenous to smokng: f smokers are more lkely than non-smokers to ext the labor force, for example due to poor health caused by smokng, then our estmates of the wage dfferental between smokers and non-smokers may be based. We speculate that our results underestmate the actual effect of smokng on earnngs as a result of ths bas. Fnally, excludng women may result n an ncomplete computaton of the socetal cost of smokng f wage-effects of smokng dffer between men and women. 7

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21 Table : Summary statstcs of the man varables used n the analyss Smokers Never smoked Mean Std. Error Mean Std. Error Log monthly wage Mother ever smoked Father ever smoked Age n years Martal status Sngle Marred Dvorced Wdowed Relgous beleves Muslm Chrstan Orthodox Chrstan Catholc Bektashan Other relgons Educaton Prmary Secondary general educaton Vocatonal educaton 2-3 years Vocatonal educaton 4-5 years Unversty dploma Speaks Englsh Speaks Italan Speaks Greek Hours worked per week Household characterstcs Household sze Share of chldren 0 to 6 years Share of chldren 7 to 4 years Share of elderly Urban household Educaton of the father Prmary Secondary general educaton Vocatonal educaton 2-3 years Vocatonal educaton 4-5 years Unversty dploma Educaton of the mother Prmary Secondary general educaton Vocatonal educaton 2-3 years Vocatonal educaton 4-5 years Unversty dploma Number of observatons

22 Table 2: 2SLS estmaton of the effect of smokng on wages. OLS 2SLS Frst Stage Second Stage Coeff. Std. Err Coeff. Std. Err Coeff. Std.Err Instrument: Father smoked 0.03 * Instrument: Mother smoked 0.53 *** Current smoker * Respondents who never smoked Reference category Age * * * 0.05 Age 2 / * * * 0.3 Age 3 / * * * 0.09 Martal status Sngle Reference category Marred * * Dvorced/Wdowed Relgous beleves Muslm Reference category Chrstan Orthodox Chrstan Catholc * Bektashan Other * Educaton Prmary Reference category Secondary general educaton * Vocatonal educaton 2-3 years Vocatonal educaton 4-5 years 0.0 ** * Unversty dploma *** * *** Speaks Englsh *** *** Speaks Italan Speaks Greek 0.86 *** *** Log hours worked per week *** *** Household characterstcs Log household sze Log household sze Urban household Share of chldren 0 to 6 years * * 0.28 Share of chldren 7 to 4 years Share of elderly Constant * F-statstc for excluded nstruments (P>F) 6.9 (0.000) R Sargan overd test (χ 2 ) 0.00 (0.98) Number of observatons Note: * s sgnfcant at 0% level; ** at 5% level; *** at % level. Regressons also nclude complete set of geographc dummy varables for the 38 dstrcts and a set of dummy varables reflectng educatonal achevements of respondent s parents. ndcates jont sgnfcance of coeffcents at 0% level. 22

23 Table 3: FIML estmaton of the swtchng regresson model. Probablty to smoke Wage of smokers Wage of never smokers Coeff. Std. Err. Coeff. Std. Err. Coeff. Std. Err. Instrument: Father smoked * 0.44 Instrument: Mother smoked *** Age * * 0.06 Age 2 / * * 0.60 Age 3 / * * 0.35 Martal status Sngle Reference Category Marred * Dvorced/Wdowed Relgous beleves Muslm Reference Category Chrstan Orthodox Chrstan Catholc * Bektashan Others * Educaton Prmary Reference Category Secondary general educaton * Vocatonal educaton 2-3 years Vocatonal educaton 4-5 years * Unversty dploma * * *** Speaks Englsh *** * Speaks Italan * Speaks Greek *** Log hours worked per week *** *** Household characterstcs Log household sze Log household sze Urban household Share of chldren 0 to 6 years ** 0.6 Share of chldren 7 to 4 years Share of elderly Constant * σ, ρ, * ** 0.09 LR test of ndependent equatons χ2 (Prob> χ2) ** 0.02 Number of observatons 588 Note: * s sgnfcant at 0% level; ** at 5% level; *** at % level. Regressons also nclude complete set of geographc dummy varables for the 38 dstrcts and a set of dummy varables reflectng educatonal achevements of mother and father of the respondents. ndcates jont sgnfcance of coeffcents at 0% level. 23