EMPLOYMENT AND THE DISTRIBUTION OF INCOME. Andrés Velasco
|
|
- Mervin Patrick
- 5 years ago
- Views:
Transcription
1 EMPLOYMENT AND THE DISTRIBUTION OF INCOME Adrés Vlasco Ju 2011
2 Motivatio My xpric as Fiac Miistr Chil: hatd discussios o iquality. But... Focus oly o th wag distributio Discussios o th shap of th wag distributio vry idological: grat mor hat tha light Littl rcogitio that wag distributio oft chags slowly, alog with its fudamtal dtrmiats (g. ducatio) Cavat: focus today o distributio of labor icom. Govrmt trasfr policy ca ad dos hav a larg impact o iquality, but that is wll udrstood
3 Motivatio (cot.) Ca w do bttr? O altrativ: focus o mploymt prformac Thr ar larg diffrcs i this prformac, v amog coutris of similar pr-capita icom Ar thr low hagig fruit hr? Tim advatag Cavat: wh thikig about improvig mploymt prformac, also d to gt away from idological divids Right: mak labor markt flxibl ad vrythig will b ok Lft: hac collctiv bargaiig ad vrythig will b ok
4 I. Th issus
5 Th issu To masur iquality w oft us th distributio of pr capita houshold icom (PCHY) If workig is a biary choic, for houshold j PCHY M j = umbr of popl workig i houshold N j = umbr of mmbrs of houshold Y ij = icom of prso i If all workig popl rciv th sam icom, M Y ij i= j = 1 N j YjM PCHY j = N j Housholds diffr gratly ot oly i thir Y ij, but i thir M j ad N j as wll. Also i th umbr of hours thy work, ot cosidrd hr. j
6 Today Focus o th implicatios of variatios i M j ad N j o th distributio of icom If M j ad N j ar uqually distributd ad if N j varis gativly with Y j ad M j varis positivly with Y j th iquality i PCHY ca b vry larg idd Mor a pla for mor rsarch tha a prstatio of a fiishd rsarch projct
7 This issu i th litratur Prst, but ot ctral, i th litratur o th microdyamics of icom distributio Bourguigo, Frrira ad Lustig (1998) Bourguigo, Frrira ad Lit (2002) Székly ad Hilgrt (2000) Largly abst from flagship publicatios 2006 WDR: Equity ad Dvlopmt 1999 IDB: Facig up to Iquality i Lati Amrica 2004 IDB: Good Jobs Watd Pla: focus o this!
8 Th road map I. Th issus II. Employmt rats ad th distributio of mploymt: cross coutry vidc III. Chil: th distributio of mploymt ad icom IV. Chil: th distributioal impact of chags i mploymt rats V. Low icom housholds with low mploymt rats: what ar thy lik? VI. Ttativ policy implicatios
9 II. Employmt rats ad th distributio of mploymt: cross coutry vidc
10 Employmt rats amog th (mostly) rich T u rk y H u g a ry Ita ly S p a i C h il M x ic o P o la d G r c E u ro p Ir la d B lg iu m S lo v a k R p u b lic O E C D c o u tri s E u ro p a U io 1 9 K o r a N o rth A m ric a E u ro p a U io 1 5 F ra c U it d S ta t s G 7 c o u tri s E sto ia L u x m b o u rg P o rtu g a l C z c h R p u b lic S lo v ia O c a ia U it d K i g d o m A u stra lia F i la d A u stria G rm a y C a a d a Ja p a N th rla d s D m a rk N w Z a la d S w d N o rw a y S w itz rla d Ic la d Mals Fmals Total Sourc: OECD Employmt rat (25-64), OECD Coutris
11 Employmt rats amog th ot-so rich Employmt rat (25-64), Lati Amrica Mal Fmal Total Sourc: Ow calculatios usig coutry s coomic survys
12 Th uqual distributio of mploymt Employmt rat by icom dcil Mxico Uruguay Argtia Brasil Chil Sourc: Ow calculatios usig coutry s coomic survys
13 III. Chil: th distributio of mploymt ad icom
14 Chil: icom dist. amog thos who work Mothly icom thos who work (dollars) /10 ratio: Sourc: Ow calculatios usig CASEN 2009.
15 Chil: houshold icom distributio Mothly houshold icom (dollars) /10 ratio: 46, Sourc: Ow calculatios usig CASEN 2009.
16 Chil: pr capita houshold icom dist. Mothly houshold icom pr capita (dollars) /10 ratio: 78, Sourc: Ow calculatios usig CASEN 2009.
17 Chil: a sad distributioal story Mothly icom pr capita, total houshold icom ad icom of thos who work (US dollars) /10 ratio: /10 ratio: 46,2 10/10 ratio: 78,5, Gii: Icom pr capita Icom of thos who work Houshold icom Sourc: Ow calculatios usig CASEN 2009.
18 Mssag Th umbr of popl who work pr houshold mak a big diffrc Th umbr of mmbrs of th houshold mak a big diffrc Ad both ar vry uvly distributd accross icom dcils
19 Th uqual distributio of jobs Houshold siz, jobs pr houshold ad jobs pr capita /10 ratio: 0,8 10/10 ratio: 3,2 10/10 ratio: 4, Sourc: Ow calculatios usig CASEN Houshold siz Jobs pr houshold Jobs pr capita
20 IV. Chil: th distributioal impact of chags i mploymt rats
21 Simulatio 1 Tak all housholds with a pr capita icom lss tha th atioal avrag Assum that i ach of thm th umbr of popl (18-64) who work is qual to th atioal avrag Thos who bgi workig mak th avrag of what popl alrady mad i that houshold If thr was o o workig, th trat maks th avrag wag for that dcil Cosidr two cass: fixd wags (uppr boud for ffct) ad wags that adjust (lowr boud)
22 Equilibrium i th markt for labor S W high A C W low B D, D L low L high
23 Simulatio 1: Rsults % 150% 100% 50% 0% Bfor Aftr: Costat wags Aftr: No-costat wags Costat wags No-costat wags 10/10 ratio = 78,5, Gii = 0,584 10/10 ratio = 32.3, Gii = 0,541 10/10 ratio = 34.9, Gii = 0,567
24 Simulatio 2 Tak all housholds with a pr capita icom lss tha th atioal avrag Assum that i ach of thm th umbr of popl (18-64) who work is qual to th atioal avrag I additio, assum that i ach of ths housholds all workrs work 45 hours a wk Thos who bgi workig mak th avrag hourly wag i that houshold If thr was o o workig, th trat maks th avrag hourly wag for that dcil Cosidr two cass: fixd wags (uppr boud for ffct) ad wags that adjust (lowr boud)
25 Simulatio 2: Rsults % 300% 200% 100% 0% Bfor Aftr: Costat wags Aftr: No-costat wags Costat wags No-costat wags 10/10 ratio = 78,5, Gii = 0,584 10/10 ratio = 21.5, Gii = 0,534 10/10 ratio = 17,5, Gii = 0,547
26 Simulatio 3 Tak all housholds with a pr capita icom lss tha th atioal avrag Assum that i ach of thm th umbr of popl (18-64) who work is qual to th umbr i dcil 10 I additio, assum that i ach of ths housholds all workrs work 45 hours a wk Thos who bgi workig mak th avrag hourly wag i that houshold If thr was o o workig, th trat maks th avrag hourly wag for that dcil Cosidr two cass: fixd wags (uppr boud for ffct) ad wags that adjust (lowr boud)
27 Simulatio 3: Rsults % 400% 300% 200% 100% 0% Bfor Aftr: Costat wags Aftr: No-costat wags Costat wags No-costat wags 10/10 ratio = 78,5, Gii = 0,584 10/10 ratio = 17.4, Gii = 0,512 10/10 ratio = 15,1, Gii = 0,531
28 V. Low icom housholds with low mploymt rats: what ar thy lik?
29 Poorr workrs work fwr hours Mothly hours of work (18-65 yars) Total Mals Fmals Sourc: Ow calculatios usig CASEN 2009.
30 Poorr dcils hav spcially low mploymt amog th youg Employmt rat by ag Dcil Sourc: Ow calculatios usig CASEN 2009.
31 Poor dcils hav spcially low mploymt amog wom Fmal mploymt rat by ag Dcil Sourc: Ow calculatios usig CASEN 2009.
32 Poorr dcils hav mor slf-mployd workrs, mor domstic srvats & fwr public mploys Dcil Employr Slf-mployd Public sctor Privat c ompais Domst ic srvats Sourc: Ow calculatios usig CASEN 2009.
33 Poorr dcils hav mor wom Fmal amog populatio by dcil (%) Sourc: Ow calculatios usig CASEN 2009.
34 Poorr dcils hav mor housholds with childr udr four Prctag of housholds with childr yougr tha 4 yars Sourc: Ow calculatios usig CASEN 2009.
35 Poorr dcils hav mor rural rsidts Prctag of housholds i rural aras (%) Sourc: Ow calculatios usig CASEN 2009.
36 Poorr dcils hav lss schoolig Yars of schoolig (popl ag 18-65) Sourc: Ow calculatios usig CASEN 2009.
37 Poorr dcils hav mor hadicappd popl Prctag of hadicappd popl Sourc: Ow calculatios usig CASEN 2009.
38 VI. Ttativ policy implicatios
39 What kps poor popl from rgular mploymt? Ky obsrvatio: thr is o o factor, ad thrfor thr is o o solutio You d a approach that dos mor tha simply mak th labor markt mor flxibl.
40 Possibl policy prioritis Supply sid Child car Urba, housig ad trasport policy Employmt subsidis (supply sid) Dmad sid Flxibility of workig hours ad shifts Prudc with miimum wags Employmt subsidis (dmad sid) Ati-discrimiatio lgislatio with tth Brigig supply ad dmad togthr Facilitat iformatio flows Ctraliz ifo: bolsas d trabajo Nd mor rsarch o th subjct!
41 EMPLOYMENT AND THE DISTRIBUTION OF INCOME Adrés Vlasco Ju 2011
Chapter (8) Estimation and Confedence Intervals Examples
Chaptr (8) Estimatio ad Cofdc Itrvals Exampls Typs of stimatio: i. Poit stimatio: Exampl (1): Cosidr th sampl obsrvatios, 17,3,5,1,18,6,16,10 8 X i i1 17 3 5 118 6 16 10 116 X 14.5 8 8 8 14.5 is a poit
More informationAPPENDIX: STATISTICAL TOOLS
I. Nots o radom samplig Why do you d to sampl radomly? APPENDI: STATISTICAL TOOLS I ordr to masur som valu o a populatio of orgaisms, you usually caot masur all orgaisms, so you sampl a subst of th populatio.
More information07 - SEQUENCES AND SERIES Page 1 ( Answers at he end of all questions ) b, z = n
07 - SEQUENCES AND SERIES Pag ( Aswrs at h d of all qustios ) ( ) If = a, y = b, z = c, whr a, b, c ar i A.P. ad = 0 = 0 = 0 l a l
More informationDiploma Macro Paper 2
Diploma Macro Papr 2 Montary Macroconomics Lctur 6 Aggrgat supply and putting AD and AS togthr Mark Hays 1 Exognous: M, G, T, i*, π Goods markt KX and IS (Y, C, I) Mony markt (LM) (i, Y) Labour markt (P,
More informationLearning objectives. Three models of aggregate supply. 1. The sticky-wage model 2. The imperfect-information model 3. The sticky-price model
Larig objctivs thr modls of aggrgat supply i which output dpds positivly o th pric lvl i th short ru th short-ru tradoff btw iflatio ad umploymt kow as th Phillips curv Aggrgat Supply slid 1 Thr modls
More informationReview Exercises. 1. Evaluate using the definition of the definite integral as a Riemann Sum. Does the answer represent an area? 2
MATHEMATIS --RE Itgral alculus Marti Huard Witr 9 Rviw Erciss. Evaluat usig th dfiitio of th dfiit itgral as a Rima Sum. Dos th aswr rprst a ara? a ( d b ( d c ( ( d d ( d. Fid f ( usig th Fudamtal Thorm
More informationProbability & Statistics,
Probability & Statistics, BITS Pilai K K Birla Goa Campus Dr. Jajati Kshari Sahoo Dpartmt of Mathmatics BITS Pilai, K K Birla Goa Campus Poisso Distributio Poisso Distributio: A radom variabl X is said
More informationMath 34A. Final Review
Math A Final Rviw 1) Us th graph of y10 to find approimat valus: a) 50 0. b) y (0.65) solution for part a) first writ an quation: 50 0. now tak th logarithm of both sids: log() log(50 0. ) pand th right
More informationThey must have different numbers of electrons orbiting their nuclei. They must have the same number of neutrons in their nuclei.
37 1 How may utros ar i a uclus of th uclid l? 20 37 54 2 crtai lmt has svral isotops. Which statmt about ths isotops is corrct? Thy must hav diffrt umbrs of lctros orbitig thir ucli. Thy must hav th sam
More informationSession : Plasmas in Equilibrium
Sssio : Plasmas i Equilibrium Ioizatio ad Coductio i a High-prssur Plasma A ormal gas at T < 3000 K is a good lctrical isulator, bcaus thr ar almost o fr lctros i it. For prssurs > 0.1 atm, collisio amog
More informationLECTURE 13 Filling the bands. Occupancy of Available Energy Levels
LUR 3 illig th bads Occupacy o Availabl rgy Lvls W hav dtrmid ad a dsity o stats. W also d a way o dtrmiig i a stat is illd or ot at a giv tmpratur. h distributio o th rgis o a larg umbr o particls ad
More informationChapter 2 Infinite Series Page 1 of 11. Chapter 2 : Infinite Series
Chatr Ifiit Sris Pag of Sctio F Itgral Tst Chatr : Ifiit Sris By th d of this sctio you will b abl to valuat imror itgrals tst a sris for covrgc by alyig th itgral tst aly th itgral tst to rov th -sris
More informationChapter 13 Aggregate Supply
Chaptr 13 Aggrgat Supply 0 1 Larning Objctivs thr modls of aggrgat supply in which output dpnds positivly on th pric lvl in th short run th short-run tradoff btwn inflation and unmploymnt known as th Phillips
More information5.1 The Nuclear Atom
Sav My Exams! Th Hom of Rvisio For mor awsom GSE ad lvl rsourcs, visit us at www.savmyxams.co.uk/ 5.1 Th Nuclar tom Qustio Papr Lvl IGSE Subjct Physics (0625) Exam oard Topic Sub Topic ooklt ambridg Itratioal
More informationmacro Road map to this lecture Objectives Aggregate Supply and the Phillips Curve Three models of aggregate supply W = ω P The sticky-wage model
Road map to this lctur macro Aggrgat Supply ad th Phillips Curv W rlax th assumptio that th aggrgat supply curv is vrtical A vrsio of th aggrgat supply i trms of iflatio (rathr tha th pric lvl is calld
More informationz 1+ 3 z = Π n =1 z f() z = n e - z = ( 1-z) e z e n z z 1- n = ( 1-z/2) 1+ 2n z e 2n e n -1 ( 1-z )/2 e 2n-1 1-2n -1 1 () z
Sris Expasio of Rciprocal of Gamma Fuctio. Fuctios with Itgrs as Roots Fuctio f with gativ itgrs as roots ca b dscribd as follows. f() Howvr, this ifiit product divrgs. That is, such a fuctio caot xist
More informationWorksheet: Taylor Series, Lagrange Error Bound ilearnmath.net
Taylor s Thorm & Lagrag Error Bouds Actual Error This is th ral amout o rror, ot th rror boud (worst cas scario). It is th dirc btw th actual () ad th polyomial. Stps:. Plug -valu ito () to gt a valu.
More informationChapter 14 Aggregate Supply and the Short-run Tradeoff Between Inflation and Unemployment
Chaptr 14 Aggrgat Supply and th Short-run Tradoff Btwn Inflation and Unmploymnt Modifid by Yun Wang Eco 3203 Intrmdiat Macroconomics Florida Intrnational Univrsity Summr 2017 2016 Worth Publishrs, all
More information4. Money cannot be neutral in the short-run the neutrality of money is exclusively a medium run phenomenon.
PART I TRUE/FALSE/UNCERTAIN (5 points ach) 1. Lik xpansionary montary policy, xpansionary fiscal policy rturns output in th mdium run to its natural lvl, and incrass prics. Thrfor, fiscal policy is also
More information1985 AP Calculus BC: Section I
985 AP Calculus BC: Sctio I 9 Miuts No Calculator Nots: () I this amiatio, l dots th atural logarithm of (that is, logarithm to th bas ). () Ulss othrwis spcifid, th domai of a fuctio f is assumd to b
More informationSolution to 1223 The Evil Warden.
Solutio to 1 Th Evil Ward. This is o of thos vry rar PoWs (I caot thik of aothr cas) that o o solvd. About 10 of you submittd th basic approach, which givs a probability of 47%. I was shockd wh I foud
More informationA Simple Proof that e is Irrational
Two of th most bautiful ad sigificat umbrs i mathmatics ar π ad. π (approximatly qual to 3.459) rprsts th ratio of th circumfrc of a circl to its diamtr. (approximatly qual to.788) is th bas of th atural
More informationcycle that does not cross any edges (including its own), then it has at least
W prov th following thorm: Thorm If a K n is drawn in th plan in such a way that it has a hamiltonian cycl that dos not cross any dgs (including its own, thn it has at last n ( 4 48 π + O(n crossings Th
More informationOption 3. b) xe dx = and therefore the series is convergent. 12 a) Divergent b) Convergent Proof 15 For. p = 1 1so the series diverges.
Optio Chaptr Ercis. Covrgs to Covrgs to Covrgs to Divrgs Covrgs to Covrgs to Divrgs 8 Divrgs Covrgs to Covrgs to Divrgs Covrgs to Covrgs to Covrgs to Covrgs to 8 Proof Covrgs to π l 8 l a b Divrgt π Divrgt
More informationWhere k is either given or determined from the data and c is an arbitrary constant.
Exponntial growth and dcay applications W wish to solv an quation that has a drivativ. dy ky k > dx This quation says that th rat of chang of th function is proportional to th function. Th solution is
More informationInflation and Unemployment
C H A P T E R 13 Aggrgat Supply and th Short-run Tradoff Btwn Inflation and Unmploymnt MACROECONOMICS SIXTH EDITION N. GREGORY MANKIW PowrPoint Slids by Ron Cronovich 2008 Worth Publishrs, all rights rsrvd
More informationINTRODUCTION TO SAMPLING DISTRIBUTIONS
http://wiki.stat.ucla.du/socr/id.php/socr_courss_2008_thomso_econ261 INTRODUCTION TO SAMPLING DISTRIBUTIONS By Grac Thomso INTRODUCTION TO SAMPLING DISTRIBUTIONS Itro to Samplig 2 I this chaptr w will
More informationSTIRLING'S 1 FORMULA AND ITS APPLICATION
MAT-KOL (Baja Luka) XXIV ()(08) 57-64 http://wwwimviblorg/dmbl/dmblhtm DOI: 075/МК80057A ISSN 0354-6969 (o) ISSN 986-588 (o) STIRLING'S FORMULA AND ITS APPLICATION Šfkt Arslaagić Sarajvo B&H Abstract:
More informationTime : 1 hr. Test Paper 08 Date 04/01/15 Batch - R Marks : 120
Tim : hr. Tst Papr 8 D 4//5 Bch - R Marks : SINGLE CORRECT CHOICE TYPE [4, ]. If th compl umbr z sisfis th coditio z 3, th th last valu of z is qual to : z (A) 5/3 (B) 8/3 (C) /3 (D) o of ths 5 4. Th itgral,
More informationStatistics 3858 : Likelihood Ratio for Exponential Distribution
Statistics 3858 : Liklihood Ratio for Expotial Distributio I ths two xampl th rjctio rjctio rgio is of th form {x : 2 log (Λ(x)) > c} for a appropriat costat c. For a siz α tst, usig Thorm 9.5A w obtai
More informationSection 6.1. Question: 2. Let H be a subgroup of a group G. Then H operates on G by left multiplication. Describe the orbits for this operation.
MAT 444 H Barclo Spring 004 Homwork 6 Solutions Sction 6 Lt H b a subgroup of a group G Thn H oprats on G by lft multiplication Dscrib th orbits for this opration Th orbits of G ar th right costs of H
More informationTriple Play: From De Morgan to Stirling To Euler to Maclaurin to Stirling
Tripl Play: From D Morga to Stirlig To Eulr to Maclauri to Stirlig Augustus D Morga (186-1871) was a sigificat Victoria Mathmaticia who mad cotributios to Mathmatics History, Mathmatical Rcratios, Mathmatical
More informationWashington State University
he 3 Ktics ad Ractor Dsig Sprg, 00 Washgto Stat Uivrsity Dpartmt of hmical Egrg Richard L. Zollars Exam # You will hav o hour (60 muts) to complt this xam which cosists of four (4) problms. You may us
More informationGradebook & Midterm & Office Hours
Your commnts So what do w do whn on of th r's is 0 in th quation GmM(1/r-1/r)? Do w nd to driv all of ths potntial nrgy formulas? I don't undrstand springs This was th first lctur I actually larnd somthing
More informationHow many neutrino species?
ow may utrio scis? Two mthods for dtrmii it lium abudac i uivrs At a collidr umbr of utrio scis Exasio of th uivrs is ovrd by th Fridma quatio R R 8G tot Kc R Whr: :ubblcostat G :Gravitatioal costat 6.
More informationComputing and Communications -- Network Coding
89 90 98 00 Computing and Communications -- Ntwork Coding Dr. Zhiyong Chn Institut of Wirlss Communications Tchnology Shanghai Jiao Tong Univrsity China Lctur 5- Nov. 05 0 Classical Information Thory Sourc
More informationOn a problem of J. de Graaf connected with algebras of unbounded operators de Bruijn, N.G.
O a problm of J. d Graaf coctd with algbras of uboudd oprators d Bruij, N.G. Publishd: 01/01/1984 Documt Vrsio Publishr s PDF, also kow as Vrsio of Rcord (icluds fial pag, issu ad volum umbrs) Plas chck
More information2617 Mark Scheme June 2005 Mark Scheme 2617 June 2005
Mark Schm 67 Ju 5 GENERAL INSTRUCTIONS Marks i th mark schm ar plicitly dsigatd as M, A, B, E or G. M marks ("mthod" ar for a attmpt to us a corrct mthod (ot mrly for statig th mthod. A marks ("accuracy"
More informationCourse: INS335 R - DEMOCRATIZATION Responsible Faculty: Kanet, Roger E --- Survey Comparisons --- Responses Individual INS All. Med.
Fall 0 (w Gral) Cours Ealuatios Fall 0 Uirsity of Miami Arts ad cics Cours: I5 R - DEMOCRATIZATIO Rsposibl Faculty: Rogr at Dpartmt: I Rsposs / Expctd: 8 / (7%) Orall : 7 5 - Poit Lirt cal (UM) (79 rsposs)
More informationPPS (Pottial Path Spac) i y i l j Vij (2) H x PP (Pottial Path ra) (gravity-typ masur) i i i j1 cij (1) D j j c ij ij 4)7) 8), 9) D j V ij j i 198 1)1
1 2 3 1 (68-8552 4 11) E-mail: taimoto@ss.tottori-u.ac.jp 2 (68-8552 4 11) 3 (657-851 1-1) Ky Words: accssibility, public trasportatio plaig, rural aras, tim allocatio, spac-tim prism 197 Hady ad Nimir
More informationph People Grade Level: basic Duration: minutes Setting: classroom or field site
ph Popl Adaptd from: Whr Ar th Frogs? in Projct WET: Curriculum & Activity Guid. Bozman: Th Watrcours and th Council for Environmntal Education, 1995. ph Grad Lvl: basic Duration: 10 15 minuts Stting:
More informationInheritance Gains in Notional Defined Contributions Accounts (NDCs)
Company LOGO Actuarial Tachrs and Rsarchrs Confrnc Oxford 14-15 th July 211 Inhritanc Gains in Notional Dfind Contributions Accounts (NDCs) by Motivation of this papr In Financial Dfind Contribution (FDC)
More informationHomework #3. 1 x. dx. It therefore follows that a sum of the
Danil Cannon CS 62 / Luan March 5, 2009 Homwork # 1. Th natural logarithm is dfind by ln n = n 1 dx. It thrfor follows that a sum of th 1 x sam addnd ovr th sam intrval should b both asymptotically uppr-
More informationChapter Five. More Dimensions. is simply the set of all ordered n-tuples of real numbers x = ( x 1
Chatr Fiv Mor Dimsios 51 Th Sac R W ar ow rard to mov o to sacs of dimsio gratr tha thr Ths sacs ar a straightforward gralizatio of our Euclida sac of thr dimsios Lt b a ositiv itgr Th -dimsioal Euclida
More information22/ Breakdown of the Born-Oppenheimer approximation. Selection rules for rotational-vibrational transitions. P, R branches.
Subjct Chmistry Papr No and Titl Modul No and Titl Modul Tag 8/ Physical Spctroscopy / Brakdown of th Born-Oppnhimr approximation. Slction ruls for rotational-vibrational transitions. P, R branchs. CHE_P8_M
More informationNarayana IIT Academy
INDIA Sc: LT-IIT-SPARK Dat: 9--8 6_P Max.Mars: 86 KEY SHEET PHYSIS A 5 D 6 7 A,B 8 B,D 9 A,B A,,D A,B, A,B B, A,B 5 A 6 D 7 8 A HEMISTRY 9 A B D B B 5 A,B,,D 6 A,,D 7 B,,D 8 A,B,,D 9 A,B, A,B, A,B,,D A,B,
More informationIndependent Domination in Line Graphs
Itratoal Joural of Sctfc & Egrg Rsarch Volum 3 Issu 6 Ju-1 1 ISSN 9-5518 Iddt Domato L Grahs M H Muddbhal ad D Basavarajaa Abstract - For ay grah G th l grah L G H s th trscto grah Thus th vrtcs of LG
More informationln x = n e = 20 (nearest integer)
H JC Prlim Solutios 6 a + b y a + b / / dy a b 3/ d dy a b at, d Giv quatio of ormal at is y dy ad y wh. d a b () (,) is o th curv a+ b () y.9958 Qustio Solvig () ad (), w hav a, b. Qustio d.77 d d d.77
More information3.1 Atomic Structure and The Periodic Table
Sav My Exams! Th Hom of Rvisio For mor awsom GSE ad lvl rsourcs, visit us at www.savmyxams.co.uk/ 3. tomic Structur ad Th Priodic Tabl Qustio Par Lvl IGSE Subjct hmistry (060) Exam oard ambridg Itratioal
More information8. Barro Gordon Model
8. Barro Gordo Modl, -.. mi s t L mi goals of motary poliy:. Miimiz dviatios of iflatio from its optimal rat π. Try to ahiv ffiit mploymt, > Stati Phillips urv: = + π π, Loss futio L = π π + Rspos of th
More informationu x v x dx u x v x v x u x dx d u x v x u x v x dx u x v x dx Integration by Parts Formula
7. Intgration by Parts Each drivativ formula givs ris to a corrsponding intgral formula, as w v sn many tims. Th drivativ product rul yilds a vry usful intgration tchniqu calld intgration by parts. Starting
More informationToday is. first we went to the park, and then we went to the library
dhlpr Nam: Today is. Novmbr Dcmbr Jauary Fix th stc. first w wt to th park, ad th w wt to th library qustio hopful Writ th words ito th boxs. umbrs stc childr wkd Writ th hidd word. Start at o lttr ad
More informationHigh Energy Physics. Lecture 5 The Passage of Particles through Matter
High Enrgy Physics Lctur 5 Th Passag of Particls through Mattr 1 Introduction In prvious lcturs w hav sn xampls of tracks lft by chargd particls in passing through mattr. Such tracks provid som of th most
More informationSecond Handout: The Measurement of Income Inequality: Basic Concepts
Scod Hadout: Th Masurmt of Icom Iqualty: Basc Cocpts O th ormatv approach to qualty masurmt ad th cocpt of "qually dstrbutd quvalt lvl of com" Suppos that that thr ar oly two dvduals socty, Rachl ad Mart
More informationMultiple Short Term Infusion Homework # 5 PHA 5127
Multipl Short rm Infusion Homwork # 5 PHA 527 A rug is aministr as a short trm infusion. h avrag pharmacokintic paramtrs for this rug ar: k 0.40 hr - V 28 L his rug follows a on-compartmnt boy mol. A 300
More informationMONTGOMERY COLLEGE Department of Mathematics Rockville Campus. 6x dx a. b. cos 2x dx ( ) 7. arctan x dx e. cos 2x dx. 2 cos3x dx
MONTGOMERY COLLEGE Dpartmt of Mathmatics Rockvill Campus MATH 8 - REVIEW PROBLEMS. Stat whthr ach of th followig ca b itgratd by partial fractios (PF), itgratio by parts (PI), u-substitutio (U), or o of
More informationANOVA- Analyisis of Variance
ANOVA- Aalii of Variac CS 700 Comparig altrativ Comparig two altrativ u cofidc itrval Comparig mor tha two altrativ ANOVA Aali of Variac Comparig Mor Tha Two Altrativ Naïv approach Compar cofidc itrval
More informationReliability of time dependent stress-strength system for various distributions
IOS Joural of Mathmatcs (IOS-JM ISSN: 78-578. Volum 3, Issu 6 (Sp-Oct., PP -7 www.osrjourals.org lablty of tm dpdt strss-strgth systm for varous dstrbutos N.Swath, T.S.Uma Mahswar,, Dpartmt of Mathmatcs,
More informationdr Bartłomiej Rokicki Chair of Macroeconomics and International Trade Theory Faculty of Economic Sciences, University of Warsaw
dr Bartłomij Rokicki Chair of Macroconomics and Intrnational Trad Thory Faculty of Economic Scincs, Univrsity of Warsaw dr Bartłomij Rokicki Opn Economy Macroconomics Small opn conomy. Main assumptions
More informationy = 2xe x + x 2 e x at (0, 3). solution: Since y is implicitly related to x we have to use implicit differentiation: 3 6y = 0 y = 1 2 x ln(b) ln(b)
4. y = y = + 5. Find th quation of th tangnt lin for th function y = ( + ) 3 whn = 0. solution: First not that whn = 0, y = (1 + 1) 3 = 8, so th lin gos through (0, 8) and thrfor its y-intrcpt is 8. y
More information3 a b c km m m 8 a 3.4 m b 2.4 m
Chaptr Exris A a 9. m. m. m 9. km. mm. m Purpl lag hapr y 8p 8m. km. m Th triangl on th right 8. m 9 a. m. m. m Exris B a m. m mm. km. mm m a. 9 8...8 m. m 8. 9 m Ativity p. 9 Pupil s own answrs Ara =
More informationPURE MATHEMATICS A-LEVEL PAPER 1
-AL P MATH PAPER HONG KONG EXAMINATIONS AUTHORITY HONG KONG ADVANCED LEVEL EXAMINATION PURE MATHEMATICS A-LEVEL PAPER 8 am am ( hours) This papr must b aswrd i Eglish This papr cosists of Sctio A ad Sctio
More informationLectures 9 IIR Systems: First Order System
EE3054 Sigals ad Systms Lcturs 9 IIR Systms: First Ordr Systm Yao Wag Polytchic Uivrsity Som slids icludd ar xtractd from lctur prstatios prpard by McCllla ad Schafr Lics Ifo for SPFirst Slids This work
More informationSummer Reading Activities!
HOOT FLUSH SCAT CHOMP From Bstslling Author Summr Rading Activitis! Flush Word Find Can you find all 14 words in th puzzl blow? S W I M E N J L P H S P A R R D A Z A G A Z E I B H O T L V S C N U D H I
More informationProbability Translation Guide
Quick Guid to Translation for th inbuilt SWARM Calculator If you s information looking lik this: Us this statmnt or any variant* (not th backticks) And this is what you ll s whn you prss Calculat Th chancs
More informationHow many neutrons does this aluminium atom contain? A 13 B 14 C 27 D 40
alumiium atom has a uclo umbr of 7 ad a roto umbr of 3. How may utros dos this alumiium atom cotai? 3 4 7 40 atom of lmt Q cotais 9 lctros, 9 rotos ad 0 utros. What is Q? calcium otassium strotium yttrium
More informationKISS: A Bit Too Simple. Greg Rose
KI: A Bit Too impl Grg Ros ggr@qualcomm.com Outli KI radom umbr grator ubgrators Efficit attack N KI ad attack oclusio PAGE 2 O approach to PRNG scurity "A radom umbr grator is lik sx: Wh it's good, its
More informationY 0. Standing Wave Interference between the incident & reflected waves Standing wave. A string with one end fixed on a wall
Staning Wav Intrfrnc btwn th incint & rflct wavs Staning wav A string with on n fix on a wall Incint: y, t) Y cos( t ) 1( Y 1 ( ) Y (St th incint wav s phas to b, i.., Y + ral & positiv.) Rflct: y, t)
More informationH2 Mathematics Arithmetic & Geometric Series ( )
H Mathmatics Arithmtic & Gomtric Sris (08 09) Basic Mastry Qustios Arithmtic Progrssio ad Sris. Th rth trm of a squc is 4r 7. (i) Stat th first four trms ad th 0th trm. (ii) Show that th squc is a arithmtic
More information6.1 Integration by Parts and Present Value. Copyright Cengage Learning. All rights reserved.
6.1 Intgration by Parts and Prsnt Valu Copyright Cngag Larning. All rights rsrvd. Warm-Up: Find f () 1. F() = ln(+1). F() = 3 3. F() =. F() = ln ( 1) 5. F() = 6. F() = - Objctivs, Day #1 Studnts will b
More informationEconomics 201b Spring 2010 Solutions to Problem Set 3 John Zhu
Economics 20b Spring 200 Solutions to Problm St 3 John Zhu. Not in th 200 vrsion of Profssor Andrson s ctur 4 Nots, th charactrization of th firm in a Robinson Cruso conomy is that it maximizs profit ovr
More informationProblem Set 6 Solutions
6.04/18.06J Mathmatics for Computr Scinc March 15, 005 Srini Dvadas and Eric Lhman Problm St 6 Solutions Du: Monday, March 8 at 9 PM in Room 3-044 Problm 1. Sammy th Shark is a financial srvic providr
More information1973 AP Calculus BC: Section I
97 AP Calculus BC: Scio I 9 Mius No Calculaor No: I his amiaio, l dos h aural logarihm of (ha is, logarihm o h bas ).. If f ( ) =, h f ( ) = ( ). ( ) + d = 7 6. If f( ) = +, h h s of valus for which f
More informationExchange rates in the long run (Purchasing Power Parity: PPP)
Exchang rats in th long run (Purchasing Powr Parity: PPP) Jan J. Michalk JJ Michalk Th law of on pric: i for a product i; P i = E N/ * P i Or quivalntly: E N/ = P i / P i Ida: Th sam product should hav
More informationEECE 301 Signals & Systems Prof. Mark Fowler
EECE 301 Signals & Systms Prof. Mark Fowlr ot St #21 D-T Signals: Rlation btwn DFT, DTFT, & CTFT 1/16 W can us th DFT to implmnt numrical FT procssing This nabls us to numrically analyz a signal to find
More informationMotivation. We talk today for a more flexible approach for modeling the conditional probabilities.
Baysia Ntworks Motivatio Th coditioal idpdc assuptio ad by aïv Bays classifirs ay s too rigid spcially for classificatio probls i which th attributs ar sowhat corrlatd. W talk today for a or flibl approach
More informationRestricted Factorial And A Remark On The Reduced Residue Classes
Applid Mathmatics E-Nots, 162016, 244-250 c ISSN 1607-2510 Availabl fr at mirror sits of http://www.math.thu.du.tw/ am/ Rstrictd Factorial Ad A Rmark O Th Rducd Rsidu Classs Mhdi Hassai Rcivd 26 March
More informationOn the approximation of the constant of Napier
Stud. Uiv. Babş-Bolyai Math. 560, No., 609 64 O th approximatio of th costat of Napir Adri Vrscu Abstract. Startig from som oldr idas of [] ad [6], w show w facts cocrig th approximatio of th costat of
More information5. B To determine all the holes and asymptotes of the equation: y = bdc dced f gbd
1. First you chck th domain of g x. For this function, x cannot qual zro. Thn w find th D domain of f g x D 3; D 3 0; x Q x x 1 3, x 0 2. Any cosin graph is going to b symmtric with th y-axis as long as
More informationChapter 4: Exponential and Logarithmic Functions
Erciss. 7 EXERCISES. Chatr : Eotial a Logarithmic Fuctios. a. c.. a. c. 7.89. a. 0.5 /.69 c. 5 5 + ( ). a. 5 5 5 5 5 + ( ) 5 c. + 0.086 0.050 /.96 5 ( ) + 5 + 6 + ( ) 5. 6. 7. 8. 9. 5.697 0. 0.9. a.. a.
More informationLECTURE 6 TRANSFORMATION OF RANDOM VARIABLES
LECTURE 6 TRANSFORMATION OF RANDOM VARIABLES TRANSFORMATION OF FUNCTION OF A RANDOM VARIABLE UNIVARIATE TRANSFORMATIONS TRANSFORMATION OF RANDOM VARIABLES If s a rv wth cdf F th Y=g s also a rv. If w wrt
More informationPROOF OF FIRST STANDARD FORM OF NONELEMENTARY FUNCTIONS
Intrnational Journal Of Advanc Rsarch In Scinc And Enginring http://www.ijars.com IJARSE, Vol. No., Issu No., Fbruary, 013 ISSN-319-8354(E) PROOF OF FIRST STANDARD FORM OF NONELEMENTARY FUNCTIONS 1 Dharmndra
More informationorbiting electron turns out to be wrong even though it Unfortunately, the classical visualization of the
Lctur 22-1 Byond Bohr Modl Unfortunatly, th classical visualization of th orbiting lctron turns out to b wrong vn though it still givs us a simpl way to think of th atom. Quantum Mchanics is ndd to truly
More informationnd the particular orthogonal trajectory from the family of orthogonal trajectories passing through point (0; 1).
Eamn EDO. Givn th family of curvs y + C nd th particular orthogonal trajctory from th family of orthogonal trajctoris passing through point (0; ). Solution: In th rst plac, lt us calculat th di rntial
More informationThe Ramsey Model. Reading: Firms. Households. Behavior of Households and Firms. Romer, Chapter 2-A;
Th Ramsy Modl Rading: Romr, Chaptr 2-A; Dvlopd by Ramsy (1928), latr dvlopd furthr by Cass (1965) and Koopmans (1965). Similar to th Solow modl: labor and knowldg grow at xognous rats. Important diffrnc:
More informationCorrelation in tree The (ferromagnetic) Ising model
5/3/00 :\ jh\slf\nots.oc\7 Chaptr 7 Blf propagato corrlato tr Corrlato tr Th (frromagtc) Isg mol Th Isg mol s a graphcal mol or par ws raom Markov fl cosstg of a urct graph wth varabls assocat wth th vrtcs.
More informationBlackbody Radiation. All bodies at a temperature T emit and absorb thermal electromagnetic radiation. How is blackbody radiation absorbed and emitted?
All bodis at a tmpratur T mit ad absorb thrmal lctromagtic radiatio Blackbody radiatio I thrmal quilibrium, th powr mittd quals th powr absorbd How is blackbody radiatio absorbd ad mittd? 1 2 A blackbody
More informationS U E K E AY S S H A R O N T IM B E R W IN D M A R T Z -PA U L L IN. Carlisle Franklin Springboro. Clearcreek TWP. Middletown. Turtlecreek TWP.
F R A N K L IN M A D IS O N S U E R O B E R T LE IC H T Y A LY C E C H A M B E R L A IN T W IN C R E E K M A R T Z -PA U L L IN C O R A O W E N M E A D O W L A R K W R E N N LA N T IS R E D R O B IN F
More informationCOHORT MBA. Exponential function. MATH review (part2) by Lucian Mitroiu. The LOG and EXP functions. Properties: e e. lim.
MTH rviw part b Lucian Mitroiu Th LOG and EXP functions Th ponntial function p : R, dfind as Proprtis: lim > lim p Eponntial function Y 8 6 - -8-6 - - X Th natural logarithm function ln in US- log: function
More information7' The growth of yeast, a microscopic fungus used to make bread, in a test tube can be
N Sction A: Pur Mathmatics 55 marks] / Th rgion R is boundd by th curv y, th -ais, and th lins = V - +7 and = m, whr m >. Find th volum gnratd whn R is rotatd through right angls about th -ais, laving
More information600 Billy Smith Road, Athens, VT
600 Billy Smith Road, Athens, VT Curtis Trousdale, Owner, Broker, Realtor Cell: 802-233-5589 curtis@preferredpropertiesvt.com 2004 Williston Road, South Burlington VT 05403 www.preferredpropertiesvt.com
More information3 2x. 3x 2. Prepared by Vince Zaccone For Campus Learning Assistance Services at UCSB
Math B Intgration Rviw (Solutions) Do ths intgrals. Solutions ar postd at th wbsit blow. If you hav troubl with thm, sk hlp immdiatly! () 8 d () 5 d () d () sin d (5) d (6) cos d (7) d www.clas.ucsb.du/staff/vinc
More informationgender mains treaming in Polis h practice
gender mains treaming in Polis h practice B E R L IN, 1 9-2 1 T H A P R IL, 2 O O 7 Gender mains treaming at national level Parliament 25 % of women in S ejm (Lower Chamber) 16 % of women in S enat (Upper
More informationBrief Introduction to Statistical Mechanics
Brif Introduction to Statistical Mchanics. Purpos: Ths nots ar intndd to provid a vry quick introduction to Statistical Mchanics. Th fild is of cours far mor vast than could b containd in ths fw pags.
More informationEEO 401 Digital Signal Processing Prof. Mark Fowler
EEO 401 Digital Signal Procssing Prof. Mark Fowlr Dtails of th ot St #19 Rading Assignmnt: Sct. 7.1.2, 7.1.3, & 7.2 of Proakis & Manolakis Dfinition of th So Givn signal data points x[n] for n = 0,, -1
More informationWhat are those βs anyway? Understanding Design Matrix & Odds ratios
Ral paramtr stimat WILD 750 - Wildlif Population Analysis of 6 What ar thos βs anyway? Undrsting Dsign Matrix & Odds ratios Rfrncs Hosmr D.W.. Lmshow. 000. Applid logistic rgrssion. John Wily & ons Inc.
More informationSearch sequence databases 3 10/25/2016
Sarch squnc databass 3 10/25/2016 Etrm valu distribution Ø Suppos X is a random variabl with probability dnsity function p(, w sampl a larg numbr S of indpndnt valus of X from this distribution for an
More informationExiting from QE. Fumio Hayashi and Junko Koeda. for presentation at SF Fed Conference. March 28, 2014
Fumio Hayashi an Junko Koa Exiting from QE March 28, 214, 1 / 29 Exiting from QE Fumio Hayashi an Junko Koa for prsntation at SF F Confrnc March 28, 214 To gt start... h^ : Fumio Hayashi an Junko Koa Exiting
More information1 Minimum Cut Problem
CS 6 Lctur 6 Min Cut and argr s Algorithm Scribs: Png Hui How (05), Virginia Dat: May 4, 06 Minimum Cut Problm Today, w introduc th minimum cut problm. This problm has many motivations, on of which coms
More informationINTEGRATION BY PARTS
Mathmatics Rvision Guids Intgration by Parts Pag of 7 MK HOME TUITION Mathmatics Rvision Guids Lvl: AS / A Lvl AQA : C Edcl: C OCR: C OCR MEI: C INTEGRATION BY PARTS Vrsion : Dat: --5 Eampls - 6 ar copyrightd
More information