%PDF-1.5 % 46 0 obj <> endobj 55 0 obj <>/Filter/FlateDecode/ID[<8DB011C182AC476AA6A8190C4A08CFDC><43C6D2C0358F42C989A14EA07DD8D6D4>]/Index[46 19]/Info 45 0 R/Length 68/Prev 185455/Root 47 0 R/Size 65/Type/XRef/W[1 3 1]>>stream hbbd```b``""A$W= H2(>10uEg`\ Zh endstream endobj startxref 0 %%EOF 64 0 obj <>stream hb```"f+   @=mL ى5 KYSZ:-> endobj 48 0 obj <>/ExtGState<>/Font<>/ProcSet[/PDF/Text]>>/Rotate 0/Type/Page>> endobj 49 0 obj <>stream hޜmo0}41N"UhQMU?dA iώC/@e8ܝ; 2d "(D"ŀ8Ł@bi qqsvF NJ\UaGJ'z2J>ԛ$cT MkM.I֚RkW9fM@\aŲ8'hHFy@p2*z0(z$2RJG*MJr0I;qkR`Uϛxk2Iz2V-7-} խ 6\i"XZb6l]I2-UqQyV,mV*kG٦ty~M I19-_q=]r +j<4#8?ߐssܡb B/V(3c)ՎF)ˆaT1$S0m{ikaB %x !D.4<x5?D/[YVteIf#E[ou4- )6yY=RX+koDۗcT{w'Z֭Bp볩g'9ۧm6UMi)?8j8WzQ,|Y=jag^I=wKg}FN?=nbomtl4}>;"o,@0geah/C|U endstream endobj 50 0 obj <>stream BT /CS0 cs 0 0 0 scn /GS0 gs /TT0 1 Tf 12 0 0 12 218.6719 723.36 Tm (University of Colorado at 鶹ӰԺ)Tj ( )Tj 1.723 -1.14 Td (Department of Economics)Tj ( )Tj /TT1 1 Tf 5.554 -1.16 Td ( )Tj ET q 66.72 679.2 176.4 13.92 re W n BT 12 0 0 12 72 682.08 Tm (Prof. Brian Cadena)Tj ET Q q 66.72 679.2 176.4 13.92 re W n BT 12 0 0 12 164.3086 682.08 Tm ( )Tj ET Q q 243.12 679.2 296.88 13.92 re W n BT 12 0 0 12 281.973 682.08 Tm (ECON)Tj ( )Tj (8848: Applied Microeconometrics, )Tj (Fall)Tj 18.802 0 Td ( )Tj (2016)Tj ( )Tj ET Q q 66.72 665.52 176.4 13.68 re W n BT 0 0 1 scn 12 0 0 12 72 668.16 Tm (brian.cadena@colorado.edu)Tj ET Q q 66.72 665.52 176.4 13.68 re W n BT 12 0 0 12 206.3203 668.16 Tm ( )Tj ET Q 0 0 1 scn 72 666 134.4 0.48 re f q 243.12 665.52 296.88 13.68 re W n BT 0 0 0 scn 12 0 0 12 425.9496 668.16 Tm (Syllabus and Schedule)Tj ET Q q 243.12 665.52 296.88 13.68 re W n BT 0 0 0 scn 12 0 0 12 534.5999 668.16 Tm ( )Tj ET Q q 66.72 610.32 176.4 55.2 re W n BT 0 0 0 scn 12 0 0 12 72 654.48 Tm (\(303\) 492)Tj ET Q q 66.72 610.32 176.4 55.2 re W n BT 0 0 0 scn 12 0 0 12 118.9922 654.48 Tm (-)Tj ET Q q 66.72 610.32 176.4 55.2 re W n BT 0 0 0 scn 12 0 0 12 122.9883 654.48 Tm (7908)Tj ET Q q 66.72 610.32 176.4 55.2 re W n BT 0 0 0 scn 12 0 0 12 146.9883 654.48 Tm ( )Tj ET Q BT 0 0 0 scn 12 0 0 12 72 640.56 Tm (Website: )Tj (D2L)Tj ( )Tj 0 0 1 scn 0 -1.14 TD (https://learn.colorado.edu)Tj 0 0 0 scn ( )Tj ET 0 0 1 scn 72 624.72 122.64 0.481 re f q 66.72 610.32 176.4 55.2 re W n BT 0 0 0 scn 12 0 0 12 72 612.96 Tm ( )Tj ET Q q 243.12 610.32 296.88 55.2 re W n BT 0 0 0 scn 12 0 0 12 365.2933 654.48 Tm (Office Hours: )Tj (MW)Tj ( )Tj (9)Tj (:)Tj (15)Tj (-)Tj (10)Tj (:)Tj (45)Tj ( )Tj (A)Tj (M)Tj ( )Tj ET Q BT 0 0 0 scn 12 0 0 12 451.6136 640.56 Tm (Economics )Tj (208D)Tj ( )Tj -4.277 -1.14 Td (Other times by appointment)Tj ( )Tj -27.358 -2.3 Td ( )Tj 0 -1.16 TD ( )Tj /TT0 1 Tf 15.209 -1.14 Td (Course )Tj (D)Tj (escription:)Tj ( )Tj /TT1 1 Tf -15.209 -1.16 Td (Students who are successful in this course will be well)Tj ( )Tj (prepared to conduct empirical research )Tj 0 -1.14 Td (across a broad range of fields, although the tools are used most frequen\ tly in the applied )Tj T* (microeconomics fields. The course provides a \223user\222s guide\224 to\ many of the most commonly )Tj 0 -1.14 TD (used econometric techniques, with a )Tj (heavy focus on implementation and interpretation. We will )Tj 0 -1.16 TD (begin the course with a STATA boot camp, quickly becoming familiar with \ the software )Tj 0 -1.14 TD (package including programming techniques and data management skills. We\ will then move )Tj 0 -1.16 TD (through a range of econo)Tj (metric topics, making sure to practice each technique in STATA. I )Tj 0 -1.14 TD (hope to live up to the following quotation by Edward Leamer in his artic\ le )Tj /TT2 1 Tf 29.993 0 Td (Let\222s Take the Con )Tj -29.993 -1.16 Td (out of Econometrics)Tj /TT1 1 Tf ( )Tj (\(AER, 1983\):)Tj ( )Tj T* ( )Tj /TT2 1 Tf 3 -1.16 Td (\223)Tj (Methodology, like sex, is better demonstrated than discuss)Tj 23.913 0 Td (ed)Tj (, though often better )Tj -23.913 -1.14 Td (anticipated than experienced.)Tj (\224)Tj ( )Tj /TT1 1 Tf -3 -1.16 Td ( )Tj /TT0 1 Tf 16.529 -1.14 Td (Prerequisites:)Tj ( )Tj /TT1 1 Tf -16.529 -1.16 Td (To enroll in this course, you must have a working knowledge of statistic\ s and econometrics )Tj T* (equivalent to that obtained in ECON 7818 and ECON 7828. )Tj 24.302 0 Td ( )Tj -24.302 -1.16 Td ( )Tj /TT0 1 Tf 15.626 -1.14 Td (Course Materials:)Tj ( )Tj /TT1 1 Tf -15.626 -1.16 Td (There is no required)Tj ( )Tj (textbook for this course, although)Tj ( )Tj (I will provide references to a number of )Tj T* (books and articles for the interested student.)Tj 17.634 0 Td ( )Tj ( )Tj (We will also read and discuss several articles. )Tj -17.634 -1.16 Td (Some of these articles will be \223theory\224 articles, discussing the r\ elative merits o)Tj 31.518 0 Td (f estimators or )Tj -31.518 -1.14 Td (developing and applying new ones. Others will be \223application\224 pa\ pers, usually papers that use )Tj 0 -1.16 TD (a technique we have discussed in an honest and useful way. I will also p\ rovide lecture notes, and )Tj 0 -1.14 TD (you will find these and the assigned articles )Tj 17.718 0 Td (posted or linked on the )Tj (Desire2Learn)Tj ( )Tj (website. You )Tj -17.718 -1.16 Td (should read the articles assigned prior to coming to class and be prepar\ ed to answer questions )Tj T* (and participate in discussions. )Tj (Please b)Tj (ring a copy)Tj ( )Tj (\(paper or electronic\))Tj ( )Tj (of the papers we are )Tj 0 -1.16 TD (discussing wit)Tj (h you to class.)Tj ( )Tj 0 -1.14 TD ( )Tj 0 -1.16 TD (Students are not required to purchase their own copies of STATA, althoug\ h those desiring to do )Tj 0 -1.14 TD (so qualify for a substantial discount through the University\222s GradPl\ an. More information is )Tj 0 -1.16 TD (available through a link posted on the )Tj 15.302 0 Td (Desire2Lear)Tj (n)Tj ( )Tj (website. I recommend)Tj ( )Tj (starting with)Tj ( )Tj (Stata/IC. )Tj -15.302 -1.14 Td (The price is)Tj ( )Tj ($)Tj (198)Tj ( )Tj (for a perpetual license)Tj ( )Tj (\(one that)Tj ( )Tj (never expires\))Tj (. )Tj ( )Tj T* ( )Tj 0 -1.14 TD (Note: SMALL STATA WILL BE INSUFFICIENT FOR THIS COURSE.)Tj ( )Tj 0 -1.16 TD ( )Tj 0 -1.14 TD (You will receive a copy of )Tj (the STATA documentation in PDF format if you choose t)Tj (o purchase )Tj 0 -1.16 TD (your own)Tj (. If you expect to use STATA beyond this course, you can feel free to p\ urchase a more )Tj ET endstream endobj 51 0 obj <>stream HyTSwoɞc [5laQIBHADED2mtFOE.c}08׎8GNg9w߽'0 ֠Jb  2y.-;!KZ ^i"L0- @8(r;q7Ly&Qq4j|9 V)gB0iW8#8wթ8_٥ʨQQj@&A)/g>'Kt;\ ӥ$պFZUn(4T%)뫔0C&Zi8bxEB;Pӓ̹A om?W= x-[0}y)7ta>jT7@tܛ`q2ʀ&6ZLĄ?_yxg)˔zçLU*uSkSeO4?׸c. 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Y߆M@'9j`Fd 9z/pZJYrS)z70aCtA;LեE H]V#rBFJ}t~}~W RE?rY( J7S5/'O`J0jʟ`"ey |PcSW-yڣM3tcdv)ZbB׉-b3 J$/$"!tI >&}>@p\N`+r:u(.pt)`Wml9=G痬Z25Z Y r"^fS!v ৘:bhOm4k{j6A)IV o& +;iYn-gkV3 G2Yr=8{Df޴}uhPG=$ 3T$ y4 @kehӈrӌex<ͤ ro9'8NY-rbYkH(Z"@(DZYye6<|ԞH#3Mak`AB)NWF{x\~.t FT)RM!ӄ3=cN蛛B|ѫ@-LL+@]]2mn$%S5= u/P6 fFW\nl5pвݿkig՞g#?6p2(f8r:qbۘTn1cQt KZ\|x u/FPӍZmc͋qs 9 endstream endobj 1 0 obj <>/ExtGState<>/Font<>/ProcSet[/PDF/Text]>>/Rotate 0/Type/Page>> endobj 2 0 obj <>stream BT /CS0 cs 0 0 0 scn /GS0 gs /TT0 1 Tf 12 0 0 12 72 723.36 Tm (advanced copy)Tj ( )Tj (\(SE or MP\))Tj (, but the Intercooled version will allow you to complete all the )Tj 0 -1.14 TD (requirements of this course. )Tj ( )Tj 0 -1.16 TD ( )Tj 0 -1.14 TD (I will use STATA during some l)Tj (ectures to demonstrate estimators and methods that we cover. 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All assignments will be STATA)Tj (-)Tj (based, although they)Tj ( )Tj (will require answering )Tj 0 -1.14 TD (interpretation/\223thinking\224 questions as well. )Tj 17.718 0 Td (These problem sets will not require proofs; rather, )Tj -17.718 -1.16 Td (they will ask you to)Tj ( )Tj (simulate or to demonstrate a particular property using real)Tj 31.353 0 Td (-)Tj (world or )Tj -31.353 -1.14 Td (simulated data. )Tj (Five)Tj ( )Tj (percentage points)Tj 15.606 0 Td ( )Tj (of y)Tj (our overall grade)Tj ( )Tj (will be based on whether you )Tj -15.606 -1.16 Td (complete the assignments and turn them in on time. I will also choose tw\ o assignments at )Tj T* (random to grade in depth)Tj (, and these grades will account for the remainder of your grade.)Tj 35.404 0 Td ( )Tj (Note )Tj -35.404 -1.16 Td (that the problem sets are )Tj (fairly short and simple to start and become more difficult as we tackle \ )Tj T* (more complicated material.)Tj 10.967 0 Td ( )Tj (You may work w)Tj (ith other students )Tj (on these assignments, and the )Tj -10.967 -1.16 Td (code may be identical to other students\222 submissions. )Tj 21.58 0 Td (To eliminate the temptation to free ride)Tj 15.716 0 Td (, )Tj -37.296 -1.14 Td (each student must submit his/her own copy of the problem set \(via D2L\)\ , and you should )Tj 0 -1.16 TD (indicate each of your collaborators on each problem set. )Tj /TT2 1 Tf 22.658 0 Td (Each student must answer the )Tj -22.658 -1.14 Td (\223thinking/interpretation\224 questions separately)Tj (, although you may discuss the answ)Tj (ers with other )Tj T* (students)Tj (. It is expressly forbidden to copy and paste )Tj (answers to these questions from another )Tj 0 -1.14 TD (student)Tj (, and any evidence that this occurred will result in a penalty of, at a \ minimum, zero credit )Tj 0 -1.16 TD (for that assignment.)Tj /TT0 1 Tf ( )Tj 0 -1.14 TD ( )Tj /TT1 1 Tf 0 -1.16 TD (Paper Replication/Extensi)Tj (on)Tj /TT0 1 Tf (: Unlike the )Tj (harder)Tj ( )Tj (sciences, the field of economics places a )Tj 0 -1.14 TD (relatively small weight on the value of replication. Nevertheless, econo\ mists make mistakes all )Tj 0 -1.16 TD (the time, and some of them go undiscovered forever. So, as a means to pr\ actice all of the skill)Tj 37.461 0 Td (s )Tj -37.461 -1.14 Td (we are developing, and in service of the broader good, you will replicat\ e )Tj 29.239 0 Td (the )Tj (central)Tj ( )Tj (analysis of )Tj (a )Tj -29.239 -1.16 Td (paper in a field that is of interest to you. You should choose a publish\ ed paper that relies on )Tj 0 -1.14 TD (publicly available data or on data that the authors have m)Tj 22.881 0 Td (ade freely available. )Tj (The paper\222s central )Tj -22.881 -1.16 Td (methodology)Tj ( )Tj (should be one of the methods we cover in this course.)Tj ( )Tj (You should also provide at )Tj T* (least one extension to the original work. Possible extensions include ad\ ding additional years of )Tj 0 -1.16 TD (data, running additional specifications \(e.g. functional form, RD inste\ ad of DiD, etc.\), and )Tj 0 -1.14 TD (subjecting the results to additional ro)Tj (bustness checks. Alternatively, you could use similar )Tj 0 -1.16 TD (methods in a slightly different context )Tj 15.497 0 Td (\226)Tj ( )Tj (different geography, different time period, etc.)Tj 19.353 0 Td ( )Tj (A paper )Tj -34.85 -1.14 Td (is not suitable as a replication paper if you cannot feasibly extend the\ paper. )Tj 30.628 0 Td (A hard copy of this )Tj -30.628 -1.16 Td (pap)Tj (er will be due in my office by close of business on )Tj (December)Tj ( )Tj (9)Tj (.)Tj ( )Tj (I will also ask for an )Tj 0 -1.14 TD (electronic copy so that I can submit the paper to TurnItIn.)Tj 23.076 0 Td ( )Tj -23.076 -1.16 Td ( )Tj ET endstream endobj 3 0 obj <>/ExtGState<>/Font<>/ProcSet[/PDF/Text]>>/Rotate 0/Type/Page>> endobj 4 0 obj <>stream BT /CS0 cs 0 0 0 scn /GS0 gs /TT0 1 Tf 12 0 0 12 72 723.36 Tm (Note that although this assignment requires the replication of the )Tj 26.16 0 Td (central)Tj ( )Tj (analysis from a )Tj -26.16 -1.14 Td (published paper, )Tj (you )Tj /TT1 1 Tf (may not borrow any language from the original paper without proper )Tj 0 -1.16 TD (citation. )Tj /TT0 1 Tf (I will require )Tj (that you complete and attach the department\222s academic integrity cove\ r )Tj 0 -1.14 TD (sheet for the assignment.)Tj ( )Tj 0 -1.16 TD ( )Tj 0 0 1 scn 0 -1.14 TD (http://www.colorado.edu/Economics/graduate/AcademicIntegrityAgreement.pd\ f)Tj 0 0 0 scn 32.239 0 Td ( )Tj ET 0 0 1 scn 72 652.32 386.88 0.48 re f BT 0 0 0 scn 12 0 0 12 72 640.56 Tm ( )Tj T* ( )Tj /TT2 1 Tf 0 -1.16 TD (The )Tj (Midterm )Tj /TT0 1 Tf (will cover material from the beginning of the course through )Tj 30.491 0 Td (lecture on )Tj (October )Tj -30.491 -1.14 Td (19)Tj (. The exam will take place during our normal class meetin)Tj 24.492 0 Td (g on )Tj (Monday)Tj (, )Tj (October )Tj (24)Tj (. You )Tj /TT1 1 Tf -24.492 -1.16 Td (will not)Tj /TT0 1 Tf ( )Tj (have to do any STATA programming for the midterm. Instead, the)Tj 30.188 0 Td ( )Tj (questions will focus )Tj -30.188 -1.14 Td (on the interpretation and implementation of techniques we have discussed\ . )Tj 30.075 0 Td (The questions will )Tj -30.075 -1.16 Td (thus be very similar to the interpretat)Tj (ion questions asked on the problem sets.)Tj ( )Tj (You may also be )Tj 0 -1.14 TD (asked questions about the papers that we read.)Tj ( )Tj /TT2 1 Tf 0 -1.16 TD ( )Tj 0 -1.14 TD (The )Tj (Final E)Tj (xam)Tj /TT0 1 Tf ( )Tj (will be nominally cumulative, but it will focus heavily on material cove\ red )Tj 0 -1.16 TD (after the midterm)Tj (. )Tj (It will be similar in format to the midterm. )Tj 24.91 0 Td (Our assig)Tj (ned time from the )Tj -24.91 -1.14 Td (Registrar is )Tj (4)Tj (:30)Tj (-)Tj (7)Tj (:00 )Tj (P)Tj (M on )Tj (Monday)Tj (, )Tj (December )Tj (12)Tj (.)Tj ( )Tj (University policy provides students with )Tj T* (three or more exams on the same day the right to reschedule exams follow\ ing the first two.)Tj 7.92 0 0 7.92 508.32 480.48 Tm (1)Tj 12 0 0 12 512.2871 474.96 Tm ( )Tj ( )Tj (Any )Tj -36.691 -1.14 Td (student wishing to invoke this right should notify me as soon as possibl\ e and no later than )Tj T* (September 30)Tj (. I will ask for a printed copy of your schedule to verify the conflict.\ )Tj 32.74 0 Td ( )Tj -32.74 -1.14 Td ( )Tj /TT2 1 Tf T* (Final Letter G)Tj (rades)Tj /TT0 1 Tf ( )Tj (will be a weighted average of each of the components )Tj 30.517 0 Td (listed above. Prior )Tj -30.517 -1.14 Td (to averaging, I will assign letter grades to each component based on the\ scores a good student at )Tj T* (this level could reasonably be expected to attain.)Tj 19.437 0 Td ( )Tj -19.437 -1.14 Td ( )Tj /TT2 1 Tf T* (Writing:)Tj /TT0 1 Tf ( )Tj (Please note that this course requires a great deal of writing. The goal \ of t)Tj 32.99 0 Td (he course)Tj ( )Tj (is to )Tj -32.99 -1.14 Td (prepare you to conduct and )Tj /TT1 1 Tf (to write about)Tj /TT0 1 Tf ( )Tj (original research )Tj (using)Tj ( )Tj (applied microeconomics. )Tj (As )Tj T* (you will soon find, the writing and communication components of applied \ econometrics are at )Tj 0 -1.14 TD (least as important as the actual econometric skills. In gr)Tj 22.215 0 Td (ading papers, exams, and problem sets, I )Tj -22.215 -1.16 Td (place )Tj (substantial)Tj ( )Tj (weight on students\222 ability to communicate their understanding and )Tj T* (interpretation of the methodologies and results.)Tj 18.884 0 Td ( )Tj -18.884 -1.16 Td ( )Tj /TT2 1 Tf T* (Seminar Series: )Tj /TT0 1 Tf (You are strongly encouraged to attend the Economics department )Tj 33.712 0 Td (seminar )Tj -33.712 -1.16 Td (series, especially when the speaker presents on an empirical applied mic\ ro topic. Learning to )Tj T* (conduct and present original research is the key to your success in the \ discipline. These seminars )Tj 0 -1.16 TD (are an excellent resource for you in that endeavor.)Tj 20.018 0 Td ( )Tj -20.018 -1.14 Td ( )Tj /TT2 1 Tf T* (Late Assignments/ Missed Examinations Policy)Tj (: )Tj /TT0 1 Tf (Problem Sets will be )Tj (turned in through the )Tj 0 -1.14 TD (Desire2Learn)Tj ( )Tj (website)Tj ( )Tj (where they will receive a time stamp)Tj 23.712 0 Td (.)Tj ( )Tj (All of the problem sets will be )Tj -23.712 -1.16 Td (posted on the first day of class)Tj (, )Tj (and )Tj (each)Tj ( )Tj (will be due )Tj (on a )Tj (Friday )Tj (by 5 PM)Tj (.)Tj ( )Tj (Following a 5)Tj (-)Tj (minute )Tj T* (grace period,)Tj ( )Tj (I will assign zero credit toward the \223completion\224 component of the\ Problem Set )Tj 0 -1.16 TD (grade for )Tj (any assignment turned in after the deadline)Tj (. In the event that )Tj (a late)Tj ( )Tj (problem set is )Tj 0 -1.14 TD (randomly selected to be graded in detail,)Tj 16.244 0 Td ( )Tj (I will deduct 1 point)Tj ( )Tj (\(out of 5\))Tj ( )Tj (for each)Tj ( )Tj (half )Tj (day it is )Tj -16.244 -1.16 Td (late)Tj (, and a)Tj (ssignments submitted more than 48 hours after the du)Tj (e date will receive no credit.)Tj 36.85 0 Td ( )Tj -36.85 -1.14 Td ( )Tj 0 -2.56 TD ( )Tj 10.4 0 Td ( )Tj 1.6 0 Td ( )Tj ET 72 74.4 144 0.48 re f BT 6.48 0 0 6.48 72.0001 64.56 Tm (1)Tj 9.84 0 0 9.84 75.3602 60 Tm ( )Tj 0 0 1 scn 0.004 Tc -0.004 Tw 0.254 0 Td [(h)-4.1(ttp)-4.1(://w)-8.1(w)-8.1(w)-8.1(.c)-3.1(o)-4.1(lo)-4.1(r)-1.1(a)-3.1(d)-4.1(o)-4.1(.e)-3.1(d)-4.1(u)-4.1(/p)-4.1(o)-4.1(lic)-3.1(ie)-3.1(s)-2.1(/f)-1.1(in)-4.1(a)-3.1(l)]TJ 0 Tc 0 Tw 15.749 0 Td (-)Tj 0.004 Tc -0.004 Tw 0.338 0 Td [(e)-3.1(x)-4.1(a)-3.1(m)-8.1(in)-4.1(a)-3.1(tio)-4.1(n)]TJ 0 Tc 0 Tw 5.023 0 Td (-)Tj 0.004 Tc -0.004 Tw 0.338 0 Td [(p)-4.1(o)-4.1(lic)-3.1(y)]TJ 0 0 0 scn 0 Tc 0 Tw 2.54 0 Td ( )Tj ET 0 0 1 scn 77.76 58.08 236.16 0.481 re f endstream endobj 5 0 obj <>/ExtGState<>/Font<>/ProcSet[/PDF/Text]>>/Rotate 0/Type/Page>> endobj 6 0 obj <>stream BT /CS0 cs 0 0 0 scn /GS0 gs /TT0 1 Tf 12 0 0 12 72 723.36 Tm (The paper replication must be turned in on time. )Tj 19.8 0 Td (Following a ten minute grace period, I will )Tj -19.8 -1.14 Td (apply at )Tj (least a 15 percent penalty to final projects turned in after the deadlin\ e, with greater )Tj 0 -1.16 TD (penalties likely for delays of more than 24 hours.)Tj 19.634 0 Td ( )Tj -19.634 -1.14 Td ( )Tj T* (If you miss the midterm or the final exam you will receive no credit unl\ ess you provide )Tj 0 -1.14 TD (documentation of a medical o)Tj 11.885 0 Td (r family emergency. In the case of a )Tj 14.882 0 Td (documented)Tj ( )Tj (emergency, the )Tj -26.767 -1.16 Td (missed exam will be given no weight in the calculation of the final grad\ e and other assignments )Tj T* (will be reweighted accordingly. There will be no make)Tj 22.159 0 Td (-)Tj (up exams. If you foresee any conflict )Tj -22.159 -1.16 Td (th)Tj (at will prevent you from taking an exam, please let me know as soon as p\ ossible and at least )Tj T* (two weeks beforehand.)Tj ( )Tj 0 -1.16 TD ( )Tj /TT1 1 Tf 0 -1.14 TD (A note on my role: )Tj /TT0 1 Tf (I )Tj (am)Tj ( )Tj (willing to offer you assistance with any assignment for this course, )Tj 0 -1.16 TD (including the final paper. I will strongly sug)Tj (gest, however, that you form study groups for the )Tj 0 -1.14 TD (problem sets and use the other members of your group as your initial res\ ource in solving )Tj 0 -1.16 TD (programming problems. )Tj (I will not tell you how to solve specific )Tj (coding issues)Tj ( )Tj (on the problem )Tj 0 -1.14 TD (sets, nor will I )Tj (tell yo)Tj (u whether you have answered interpretation questions properly)Tj 33.686 0 Td ( )Tj (prior to the )Tj -33.686 -1.16 Td (due date)Tj (.)Tj ( )Tj (Solutions will be provided )Tj (shortly after the deadline to turn in the assignment)Tj (.)Tj ( )Tj ( )Tj T* ( )Tj 0 -1.16 TD (I cannot generally offer help on projects that are unrelated to this cou\ rse, e.g. work y)Tj 33.821 0 Td (ou are doing )Tj -33.821 -1.14 Td (as part of your dissertation or as an RA for other faculty members. My \ goal in offering this )Tj T* (course is to create a critical mass of well)Tj (-)Tj (trained graduate students who can then continue to )Tj 0 -1.14 TD (learn more on their own and begin to serve as a resour)Tj 21.687 0 Td (ce to each o)Tj (ther. )Tj ( )Tj -2.187 -1.16 Td ( )Tj /TT1 1 Tf -19.5 -1.14 Td (Cheating:)Tj ( )Tj /TT0 1 Tf (If you copy interpretation answers from a classmate \(or previous studen\ t\) on a )Tj 0 -1.16 TD (problem set, you will receive no credit for that problem set. If you che\ at on an exam, you will )Tj 0 -1.14 TD (fail that exam. If you plagiarize even a portion of)Tj 19.659 0 Td ( )Tj (your final project, you will fail the final )Tj -19.659 -1.16 Td (project. I reserve the right to impose harsher academic sanctions up to \ and including failing the )Tj T* (course for any instance of cheating. )Tj (Also, note )Tj (that failing any )Tj (component)Tj ( )Tj (of the course makes it )Tj 0 -1.16 TD (very unlikely that you will earn a )Tj (\223)Tj (B)Tj (\224)Tj ( )Tj (or better )Tj (in the course)Tj (.)Tj /TT1 1 Tf ( )Tj ET endstream endobj 7 0 obj <>/ExtGState<>/Font<>/ProcSet[/PDF/Text]>>/Rotate 0/Type/Page>> endobj 8 0 obj <>stream BT /CS0 cs 0 0 0 scn /GS0 gs /TT0 1 Tf 12 0 0 12 257.168 723.36 Tm (Tentative Schedule)Tj ( )Tj /TT1 1 Tf -15.431 -1.14 Td ( )Tj ( )Tj 9.859 -1.46 Td (Topic)Tj ( )Tj 17.73 0 Td (Tentative Dates)Tj ( )Tj ET 66.24 706.32 0.48 0.48 re f 66.24 706.32 0.48 0.48 re f 66.72 706.32 275.04 0.48 re f 341.76 706.32 0.481 0.48 re f 342.24 706.32 197.519 0.48 re f 539.76 706.32 0.481 0.48 re f 539.76 706.32 0.481 0.48 re f 66.24 686.16 0.48 20.16 re f 341.76 686.16 0.481 20.16 re f 539.76 686.16 0.481 20.16 re f BT 12 0 0 12 72 671.52 Tm (Introduction and STATA Basics)Tj ( )Tj 22.94 0 Td (8/2)Tj (2)Tj (, 8/2)Tj (4)Tj ( )Tj ET 66.24 685.68 0.48 0.48 re f 66.72 685.68 275.04 0.48 re f 341.76 685.68 0.481 0.48 re f 342.24 685.68 197.519 0.48 re f 539.76 685.68 0.481 0.48 re f 66.24 665.52 0.48 20.16 re f 341.76 665.52 0.481 20.16 re f 539.76 665.52 0.481 20.16 re f BT 12 0 0 12 72 650.88 Tm (Advanced STATA)Tj ( )Tj 22.94 0 Td ( )Tj ET 66.24 665.04 0.48 0.481 re f 66.72 665.04 275.04 0.481 re f 341.76 665.04 0.481 0.481 re f 342.24 665.04 197.519 0.481 re f 539.76 665.04 0.481 0.481 re f 66.24 644.88 0.48 20.16 re f 341.76 644.88 0.481 20.16 re f 539.76 644.88 0.481 20.16 re f BT 12 0 0 12 108 630.24 Tm (Descriptive Statistics, Figures and Tables)Tj 16.58 0 Td ( )Tj 3.36 0 Td (8/)Tj (29)Tj ( )Tj ET 66.24 644.4 0.48 0.48 re f 66.72 644.4 275.04 0.48 re f 341.76 644.4 0.481 0.48 re f 342.24 644.4 197.519 0.48 re f 539.76 644.4 0.481 0.48 re f 66.24 624.24 0.48 20.16 re f 341.76 624.24 0.481 20.16 re f 539.76 624.24 0.481 20.16 re f BT 12 0 0 12 108 609.6 Tm (Programming )Tj (\226)Tj ( )Tj (Loops, Macros)Tj ( )Tj 19.94 0 Td (8/31)Tj ( )Tj ET 66.24 623.76 0.48 0.48 re f 66.72 623.76 275.04 0.48 re f 341.76 623.76 0.481 0.48 re f 342.24 623.76 197.519 0.48 re f 539.76 623.76 0.481 0.48 re f 66.24 603.6 0.48 20.16 re f 341.76 603.6 0.481 20.16 re f 539.76 603.6 0.481 20.16 re f BT 12 0 0 12 108 588.72 Tm (NO CLASS )Tj (\226)Tj ( )Tj (Labor Day)Tj ( )Tj 19.94 0 Td (9/)Tj (5)Tj ( )Tj ET 66.24 603.12 0.48 0.481 re f 66.72 603.12 275.04 0.481 re f 341.76 603.12 0.481 0.481 re f 342.24 603.12 197.519 0.481 re f 539.76 603.12 0.481 0.481 re f 66.24 582.96 0.48 20.16 re f 341.76 582.96 0.481 20.16 re f 539.76 582.96 0.481 20.16 re f BT 12 0 0 12 108 568.08 Tm (Simulation)Tj ( )Tj 19.94 0 Td (9/)Tj (7)Tj ( )Tj ET 66.24 582.48 0.48 0.48 re f 66.72 582.48 275.04 0.48 re f 341.76 582.48 0.481 0.48 re f 342.24 582.48 197.519 0.48 re f 539.76 582.48 0.481 0.48 re f 66.24 562.32 0.48 20.16 re f 341.76 562.32 0.481 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(,9/1)Tj (4)Tj ( )Tj ET 66.24 541.2 0.48 0.481 re f 66.72 541.2 275.04 0.481 re f 341.76 541.2 0.481 0.481 re f 342.24 541.2 197.519 0.481 re f 539.76 541.2 0.481 0.481 re f 66.24 513.6 0.48 27.599 re f 341.76 513.6 0.481 27.599 re f 539.76 513.6 0.481 27.599 re f q 66.96 485.52 274.8 27.6 re W n BT 12 0 0 12 108 502.08 Tm (Review of FWL and the meaning of )Tj ET Q q 66.96 485.52 274.8 27.6 re W n BT 12 0 0 12 108 488.16 Tm (\223controlling for\224)Tj ET Q q 66.96 485.52 274.8 27.6 re W n BT 12 0 0 12 188.3027 488.16 Tm ( )Tj ET Q BT 12 0 0 12 347.28 495.12 Tm (9/)Tj (19)Tj ( )Tj ET 66.24 513.12 0.48 0.481 re f 66.72 513.12 275.04 0.481 re f 341.76 513.12 0.481 0.481 re f 342.24 513.12 197.519 0.481 re f 539.76 513.12 0.481 0.481 re f 66.24 485.52 0.48 27.599 re f 341.76 485.52 0.481 27.599 re f 539.76 485.52 0.481 27.599 re f BT 12 0 0 12 72 470.64 Tm (The Experimental Ideal)Tj ( )Tj 22.94 0 Td ( )Tj ET 66.24 485.04 0.48 0.481 re f 66.72 485.04 275.04 0.481 re f 341.76 485.04 0.481 0.481 re f 342.24 485.04 197.519 0.481 re f 539.76 485.04 0.481 0.481 re f 66.24 464.64 0.48 20.399 re f 341.76 464.64 0.481 20.399 re f 539.76 464.64 0.481 20.399 re f q 66.96 436.56 274.8 27.6 re W n BT 12 0 0 12 108 453.12 Tm (Treatment Effects )Tj (\226)Tj ( )Tj (Potential Outcomes )Tj ET Q q 66.96 436.56 274.8 27.6 re W n BT 12 0 0 12 108 439.44 Tm (Framework)Tj ET Q q 66.96 436.56 274.8 27.6 re W n BT 12 0 0 12 163.3184 439.44 Tm ( )Tj ET Q BT 12 0 0 12 347.28 446.4 Tm (9/)Tj (21)Tj ( )Tj ET 66.24 464.16 0.48 0.481 re f 66.72 464.16 275.04 0.481 re f 341.76 464.16 0.481 0.481 re f 342.24 464.16 197.519 0.481 re f 539.76 464.16 0.481 0.481 re f 66.24 436.56 0.48 27.599 re f 341.76 436.56 0.481 27.599 re f 539.76 436.56 0.481 27.599 re f BT 12 0 0 12 108 421.92 Tm (Causality in an OLS Regression )Tj (\226)Tj ( )Tj (the CIA)Tj ( )Tj 19.94 0 Td (9/)Tj (26)Tj ( )Tj ET 66.24 436.08 0.48 0.481 re f 66.72 436.08 275.04 0.481 re f 341.76 436.08 0.481 0.481 re f 342.24 436.08 197.519 0.481 re f 539.76 436.08 0.481 0.481 re f 66.24 415.92 0.48 20.16 re f 341.76 415.92 0.481 20.16 re f 539.76 415.92 0.481 20.16 re f BT 12 0 0 12 108 401.28 Tm (Propensity Score Methods)Tj ( )Tj 19.94 0 Td (9/)Tj (28)Tj ( )Tj ET 66.24 415.44 0.48 0.48 re f 66.72 415.44 275.04 0.48 re f 341.76 415.44 0.481 0.48 re f 342.24 415.44 197.519 0.48 re f 539.76 415.44 0.481 0.48 re f 66.24 395.28 0.48 20.16 re f 341.76 395.28 0.481 20.16 re f 539.76 395.28 0.481 20.16 re f BT 12 0 0 12 72 380.64 Tm (Advanced Data )Tj (Management)Tj ( )Tj 22.94 0 Td (10/)Tj (3)Tj ( )Tj ET 66.24 394.8 0.48 0.48 re f 66.72 394.8 275.04 0.48 re f 341.76 394.8 0.481 0.48 re f 342.24 394.8 197.519 0.48 re f 539.76 394.8 0.481 0.48 re f 66.24 374.64 0.48 20.16 re f 341.76 374.64 0.481 20.16 re f 539.76 374.64 0.481 20.16 re f BT 12 0 0 12 72 360 Tm (Panel Data Models)Tj ( )Tj 22.94 0 Td ( )Tj ET 66.24 374.16 0.48 0.481 re f 66.72 374.16 275.04 0.481 re f 341.76 374.16 0.481 0.481 re f 342.24 374.16 197.519 0.481 re f 539.76 374.16 0.481 0.481 re f 66.24 354 0.48 20.16 re f 341.76 354 0.481 20.16 re f 539.76 354 0.481 20.16 re f BT 12 0 0 12 108 339.36 Tm (Difference)Tj (-)Tj (in)Tj (-)Tj (Differences)Tj ( )Tj 19.94 0 Td (10/)Tj (5)Tj (, )Tj (10/)Tj (10)Tj ( )Tj (\226)Tj ( )Tj (paper)Tj ( )Tj ET 66.24 353.52 0.48 0.48 re f 66.72 353.52 275.04 0.48 re f 341.76 353.52 0.481 0.48 re f 342.24 353.52 197.519 0.48 re f 539.76 353.52 0.481 0.48 re f 66.24 333.36 0.48 20.16 re f 341.76 333.36 0.481 20.16 re f 539.76 333.36 0.481 20.16 re f BT 12 0 0 12 108 318.72 Tm (RE, FE, FD)Tj ( )Tj 19.94 0 Td (10/)Tj (12)Tj (, )Tj (10/)Tj (17)Tj ( )Tj (\226)Tj ( )Tj (paper\(s\))Tj ( )Tj ET 66.24 332.88 0.48 0.48 re f 66.72 332.88 275.04 0.48 re f 341.76 332.88 0.481 0.48 re f 342.24 332.88 197.519 0.48 re f 539.76 332.88 0.481 0.48 re f 66.24 312.72 0.48 20.16 re f 341.76 312.72 0.481 20.16 re f 539.76 312.72 0.481 20.16 re f BT 12 0 0 12 72 298.08 Tm (MIDTERM EXAM)Tj ( )Tj 22.94 0 Td (10/)Tj (24)Tj ( )Tj ET 66.24 312.24 0.48 0.481 re f 66.72 312.24 275.04 0.481 re f 341.76 312.24 0.481 0.481 re f 342.24 312.24 197.519 0.481 re f 539.76 312.24 0.481 0.481 re f 66.24 292.08 0.48 20.16 re f 341.76 292.08 0.481 20.16 re f 539.76 292.08 0.481 20.16 re f BT 12 0 0 12 108 277.44 Tm (Variance Estimation in Panel Models)Tj 14.941 0 Td ( )Tj 4.999 0 Td (10/)Tj (19)Tj (, 10/)Tj (26)Tj ( )Tj (\226)Tj ( )Tj (paper )Tj ( )Tj ET 66.24 291.6 0.48 0.48 re f 66.72 291.6 275.04 0.48 re f 341.76 291.6 0.481 0.48 re f 342.24 291.6 197.519 0.48 re f 539.76 291.6 0.481 0.48 re f 66.24 271.44 0.48 20.16 re f 341.76 271.44 0.481 20.16 re f 539.76 271.44 0.481 20.16 re f BT 12 0 0 12 72 256.8 Tm (Instrumental Variables)Tj ( )Tj 22.94 0 Td ( )Tj ET 66.24 270.96 0.48 0.48 re f 66.72 270.96 275.04 0.48 re f 341.76 270.96 0.481 0.48 re f 342.24 270.96 197.519 0.48 re f 539.76 270.96 0.481 0.48 re f 66.24 250.8 0.48 20.16 re f 341.76 250.8 0.481 20.16 re f 539.76 250.8 0.481 20.16 re f BT 12 0 0 12 108 236.16 Tm (Basics )Tj (\226)Tj ( )Tj (Constant Treatment )Tj (Effects)Tj ( )Tj 19.94 0 Td (10/30)Tj ( )Tj ET 66.24 250.32 0.48 0.481 re f 66.72 250.32 275.04 0.481 re f 341.76 250.32 0.481 0.481 re f 342.24 250.32 197.519 0.481 re f 539.76 250.32 0.481 0.481 re f 66.24 230.16 0.48 20.16 re f 341.76 230.16 0.481 20.16 re f 539.76 230.16 0.481 20.16 re f BT 12 0 0 12 108 215.52 Tm (Local Average Treatment Effects)Tj 13.354 0 Td ( )Tj 6.586 0 Td (11/)Tj (2)Tj (, )Tj (11/)Tj (7)Tj ( )Tj (-)Tj ( )Tj (paper)Tj ( )Tj ET 66.24 229.68 0.48 0.48 re f 66.72 229.68 275.04 0.48 re f 341.76 229.68 0.481 0.48 re f 342.24 229.68 197.519 0.48 re f 539.76 229.68 0.481 0.48 re f 66.24 209.52 0.48 20.16 re f 341.76 209.52 0.481 20.16 re f 539.76 209.52 0.481 20.16 re f BT 12 0 0 12 72 194.88 Tm (NO CLASS )Tj (\226)Tj ( )Tj (Individual Meetings)Tj ( )Tj 22.94 0 Td (11/)Tj (9)Tj (, 11/)Tj (14)Tj ( )Tj ET 66.24 209.04 0.48 0.48 re f 66.72 209.04 275.04 0.48 re f 341.76 209.04 0.481 0.48 re f 342.24 209.04 197.519 0.48 re f 539.76 209.04 0.481 0.48 re f 66.24 188.88 0.48 20.16 re f 341.76 188.88 0.481 20.16 re f 539.76 188.88 0.481 20.16 re f BT 12 0 0 12 72 174.24 Tm (Regression Discontinuity)Tj ( )Tj 22.94 0 Td (11/)Tj (16)Tj (, )Tj (11/)Tj (28)Tj ( )Tj (\226)Tj ( )Tj (paper)Tj ( )Tj ET 66.24 188.4 0.48 0.481 re f 66.72 188.4 275.04 0.481 re f 341.76 188.4 0.481 0.481 re f 342.24 188.4 197.519 0.481 re f 539.76 188.4 0.481 0.481 re f 66.24 168.24 0.48 20.16 re f 341.76 168.24 0.481 20.16 re f 539.76 168.24 0.481 20.16 re f BT 12 0 0 12 72 153.6 Tm (NO CLASS )Tj (\226)Tj ( )Tj (Fall Break)Tj ( )Tj 22.94 0 Td (11/2)Tj (1)Tj (, 11/2)Tj (3)Tj ( )Tj ET 66.24 167.76 0.48 0.48 re f 66.72 167.76 275.04 0.48 re f 341.76 167.76 0.481 0.48 re f 342.24 167.76 197.519 0.48 re f 539.76 167.76 0.481 0.48 re f 66.24 147.6 0.48 20.16 re f 341.76 147.6 0.481 20.16 re f 539.76 147.6 0.481 20.16 re f BT 12 0 0 12 72 132.96 Tm (Binary Dependent Variables)Tj 11.385 0 Td ( )Tj 11.555 0 Td (11/30)Tj ( )Tj ET 66.24 147.12 0.48 0.48 re f 66.72 147.12 275.04 0.48 re f 341.76 147.12 0.481 0.48 re f 342.24 147.12 197.519 0.48 re f 539.76 147.12 0.481 0.48 re f 66.24 126.96 0.48 20.16 re f 341.76 126.96 0.481 20.16 re f 539.76 126.96 0.481 20.16 re f BT 12 0 0 12 72 112.08 Tm (Wrap)Tj (-)Tj (Up)Tj ( )Tj 22.94 0 Td (12/)Tj (5)Tj (, 12/)Tj (7)Tj ( )Tj ET 66.24 126.48 0.48 0.481 re f 66.72 126.48 275.04 0.481 re f 341.76 126.48 0.481 0.481 re f 342.24 126.48 197.519 0.481 re f 539.76 126.48 0.481 0.481 re f 66.24 106.32 0.48 20.16 re f 341.76 106.32 0.481 20.16 re f 539.76 106.32 0.481 20.16 re f BT 12 0 0 12 72 91.44 Tm (FINAL )Tj (EXAM)Tj 6.139 0 Td ( )Tj 16.801 0 Td (Monday, 12/1)Tj (2)Tj ( )Tj (4:30)Tj (-)Tj (7:00 PM)Tj ( )Tj ET 66.24 105.84 0.48 0.48 re f 66.72 105.84 275.04 0.48 re f 341.76 105.84 0.481 0.48 re f 342.24 105.84 197.519 0.48 re f 539.76 105.84 0.481 0.48 re f 66.24 85.68 0.48 20.16 re f 66.24 85.2 0.48 0.48 re f 66.24 85.2 0.48 0.48 re f 66.72 85.2 275.04 0.48 re f 341.76 85.68 0.481 20.16 re f 341.76 85.2 0.481 0.48 re f 342.24 85.2 197.519 0.48 re f 539.76 85.68 0.481 20.16 re f 539.76 85.2 0.481 0.48 re f 539.76 85.2 0.481 0.48 re f BT /TT0 1 Tf 12 0 0 12 72 74.16 Tm ( )Tj 12 0 Td ( )Tj ET endstream endobj 9 0 obj <>/ExtGState<>/Font<>/ProcSet[/PDF/Text]>>/Rotate 0/Type/Page>> endobj 10 0 obj <>stream BT /CS0 cs 0 0 0 scn /GS0 gs /TT0 1 Tf 12 0 0 12 239.6836 723.36 Tm (Other University Policies)Tj (:)Tj ( )Tj 5.526 -1.14 Td ( )Tj -19.5 -1.16 Td (Disability Accommodation)Tj ( )Tj /TT1 1 Tf 0 -1.14 TD (If you qualify for accommodations because of a disability, please submit\ to )Tj 30.353 0 Td (Prof. Cadena)Tj ( )Tj (a letter )Tj -30.353 -1.16 Td (from Disability Services in a timely manner \(for exam accommodations pr\ ovide your letter at )Tj T* (least one week prior to the exam\) so that your needs can be addressed. \ Disability Services )Tj 0 -1.16 TD (determines accommodations based on documented disabilities. Con)Tj 27.077 0 Td (tact Disability Services at )Tj -27.077 -1.14 Td (303)Tj (-)Tj (492)Tj (-)Tj (8671 or by e)Tj (-)Tj (mail at )Tj 0 0 1 scn (dsinfo@colorado.edu)Tj 0 0 0 scn (. )Tj ( )Tj ET 0 0 1 scn 216.24 624.72 103.44 0.481 re f BT 0 0 0 scn 12 0 0 12 72 612.96 Tm ( )Tj 0 -1.14 TD (f you have a temporary medical condition or injury, see)Tj 22.215 0 Td ( )Tj 0 0 1 scn (Temporary Injuries)Tj 0 0 0 scn ( )Tj (guidelines under the )Tj ET 0 0 1 scn 341.52 597.12 93.119 0.48 re f BT 0 0 0 scn 12 0 0 12 72 585.36 Tm (Quick Links at the )Tj 0 0 1 scn (Di)Tj (sability Services website)Tj 0 0 0 scn ( )Tj (and discuss your needs with)Tj ( )Tj (Prof. Cadena.)Tj ( )Tj ET 0 0 1 scn 163.92 583.2 130.801 0.48 re f BT 0 0 0 scn 12 0 0 12 72 571.68 Tm ( )Tj /TT0 1 Tf 0 -1.16 TD (Religious Observances)Tj ( )Tj /TT1 1 Tf 0 -1.14 TD (Campus policy regarding religious observances requires that faculty make\ every effort to deal )Tj 0 -1.16 TD (reasonably and fairly with all students who, because of religious oblig)Tj 28.021 0 Td (ations, have conflicts with )Tj -28.021 -1.14 Td (scheduled exams, assignments or required attendance)Tj 21.381 0 Td (. In this )Tj (course)Tj (, )Tj (please inform me no later )Tj -21.381 -1.16 Td (than two weeks prior to any conflict you foresee, sooner if possible, so\ that we may find an )Tj 0 -1.14 TD (alternative arrangement for you to compl)Tj 16.41 0 Td (ete the requirements of the course. )Tj 14.022 0 Td (See )Tj 0 0 1 scn 1.694 0 Td (campus policy )Tj ET 457.44 486.72 69.84 0.48 re f BT 12 0 0 12 72 474.96 Tm (regarding religious observances)Tj 0 0 0 scn 12.718 0 Td ( )Tj (for full details.)Tj ( )Tj ET 0 0 1 scn 72 472.8 152.64 0.481 re f BT 0 0 0 scn /TT0 1 Tf 12 0 0 12 72.0001 461.28 Tm ( )Tj 0 -1.16 TD (Classroom Behavior)Tj ( )Tj 0 -1.14 TD ( )Tj /TT1 1 Tf 0 -1.16 TD (Students and faculty each have responsibility for maintaining an appropr\ iate learning )Tj 0 -1.14 TD (environment. Those who fail to adhere to such behavioral standards may b\ e subject to discipline. )Tj 0 -1.16 TD (Professional courtesy and sensitivity are especially important with resp\ e)Tj 28.881 0 Td (ct to individuals and )Tj -28.881 -1.14 Td (topics dealing with differences of race, color, culture, religion, creed\ , politics, veteran\222s status, )Tj T* (sexual orientation, gender, gender identity and gender expression, age, \ disability, and )Tj 0 -1.14 TD (nationalities. Class rosters are provided to)Tj ( )Tj (the instructor with the student's legal name. I will )Tj 0 -1.16 TD (gladly honor your request to address you by an alternate name or gender \ pronoun. Please advise )Tj 0 -1.14 TD (me of this preference early in the semester so that I may make appropria\ te changes to my )Tj 0 -1.16 TD (records. For more )Tj (information, see the policies on )Tj 0 0 1 scn (classroom behavior)Tj 0 0 0 scn ( )Tj (and )Tj 0 0 1 scn (the student code.)Tj 0 0 0 scn ( )Tj ET 0 0 1 scn 314.64 307.2 93.6 0.481 re f 431.52 307.2 81.12 0.481 re f BT 0 0 0 scn /TT0 1 Tf 12 0 0 12 72.0001 295.68 Tm ( )Tj T* (Discrimination and Harassment)Tj ( )Tj /TT1 1 Tf 0 -1.14 TD ( )Tj 0 -1.16 TD (The 鶹ӰԺ \(CU 鶹ӰԺ\) is committed to mainta\ ining a positive )Tj 0 -1.14 TD (learning, working, and living environment. CU B)Tj (oulder will not tolerate acts of sexual )Tj 0 -1.16 TD (misconduct, discrimination, harassment or related retaliation against or\ by any employee or )Tj 0 -1.14 TD (student. CU\222s Sexual Misconduct Policy prohibits sexual assault, sexu\ al exploitation, sexual )Tj 0 -1.16 TD (harassment, intimate partner ab)Tj 12.551 0 Td (use \(dating or domestic violence\), stalking or related retaliation. )Tj -12.551 -1.14 Td (CU 鶹ӰԺ\222s Discrimination and Harassment Policy prohibits discrimin\ ation, harassment or )Tj T* (related retaliation based on race, color, national origin, sex, pregnanc\ y, age, disability, creed,)Tj 37.152 0 Td ( )Tj -37.152 -1.14 Td (religion, sexual orientation, gender identity, gender expression, vetera\ n status, political affiliation )Tj T* (or political philosophy. Individuals who believe they have been subject \ to misconduct under )Tj 0 -1.14 TD (either policy should contact the Office of Institutional Eq)Tj 22.882 0 Td (uity and Compliance \(OIEC\) at 303)Tj (-)Tj -22.882 -1.16 Td (492)Tj (-)Tj (2127. Information about the OIEC, the above referenced policies, and the\ campus resources )Tj T* (available to assist individuals regarding sexual misconduct, discriminat\ ion, harassment or related )Tj 0 -1.16 TD (retaliation can be found at t)Tj (he )Tj 0 0 1 scn (OIEC website)Tj 0 0 0 scn (.)Tj ( )Tj ET 0 0 1 scn 217.92 86.4 67.68 0.48 re f BT 0 0 0 scn /TT0 1 Tf 12 0 0 12 72.0001 74.88 Tm ( )Tj T* ( )Tj ET endstream endobj 11 0 obj <>/ExtGState<>/Font<>/ProcSet[/PDF/Text]>>/Rotate 0/Type/Page>> endobj 12 0 obj <>stream BT /CS0 cs 0 0 0 scn /GS0 gs /TT0 1 Tf 12 0 0 12 72 723.36 Tm (Academic Integrity)Tj ( )Tj /TT1 1 Tf 0 -1.14 TD ( )Tj 0 -1.16 TD (All students enrolled in a 鶹ӰԺ course are res\ ponsible f)Tj 32.77 0 Td (or knowing )Tj -32.77 -1.14 Td (and adhering to)Tj ( )Tj (the )Tj 0 0 1 scn (academic integrity policy)Tj 0 0 0 scn 18.104 0 Td ( )Tj (of the institution. Violations of the policy may )Tj ET 0 0 1 scn 167.28 679.92 121.919 0.48 re f BT 0 0 0 scn 12 0 0 12 72 668.16 Tm (include: plagi)Tj (arism, cheating, fabrication, lying, bribery, threat, unauthorized acces\ s, clicker )Tj 0 -1.14 TD (fraud, resubmission, and aiding academic dishonesty. All incidents of ac\ ademic misconduct will )Tj 0 -1.16 TD (be reported to the Honor Code Council \()Tj 0 0 1 scn (honor@colorado.edu)Tj 0 0 0 scn (; 303)Tj (-)Tj (735)Tj (-)Tj (2273\). Students who are )Tj ET 0 0 1 scn 266.4 638.4 101.28 0.481 re f BT 0 0 0 scn 12 0 0 12 72 626.88 Tm (found responsible for violating the academic integrity policy will be su\ bject to nonacademic )Tj T* (sanctions from the Honor Code Council as well as academic sanctions from\ the faculty member. )Tj 0 -1.14 TD (Additional info)Tj (rmation regarding the academic integrity policy can be found at )Tj 0 0 1 scn 0 -1.16 TD (honorcode.colorado.edu)Tj 0 0 0 scn (.)Tj ( )Tj ET 0 0 1 scn 72 583.2 115.92 0.48 re f BT 0 0 0 scn /TT0 1 Tf 12 0 0 12 72 571.68 Tm ( )Tj 12 0 Td ( )Tj ET endstream endobj 13 0 obj <>/ExtGState<>/Font<>/ProcSet[/PDF/Text]>>/Rotate 0/Type/Page>> endobj 14 0 obj <>stream BT /CS0 cs 0 0 0 scn /GS0 gs /TT0 1 Tf 12 0 0 12 273.1611 723.36 Tm (Reading List)Tj ( )Tj 2.737 -1.14 Td ( )Tj /TT1 1 Tf -19.5 -1.16 Td (The list below )Tj (provides a guide to how to get the most out of your available resources \ for this )Tj 0 -1.14 Td (course. Your most directly relevant text will be our lecture notes. Th\ ey will provide you with )Tj 0 -1.16 TD (the basics of all of the material that we cover in each class meeting. \ There )Tj 30.071 0 Td (are also two books )Tj -30.071 -1.14 Td (that I think fit nicely with the applied nature of this course and offer\ a good complement to our )Tj T* (in)Tj (-)Tj (class discussion. They are both relatively inexpensive, and I would rec\ ommend them as your )Tj 0 -1.14 TD (best additional resources for learning the t)Tj (opics we cover. I also strongly recommend having one )Tj 0 -1.16 TD (or more graduate econometrics textbooks for reference. Finally, we will\ read a few papers that )Tj 0 -1.14 TD (apply the methods we are discussing. These are listed below in bold. Ad\ ditional references that )Tj 0 -1.16 TD (we will p)Tj (robably not have time for are listed in standard font. The links are act\ ive, but you will )Tj 0 -1.14 TD (need to be on)Tj (-)Tj (campus or connected through VPN.)Tj ( )Tj 0 -1.16 TD ( )Tj /TT0 1 Tf 0 -1.14 TD (Books with an Applied Focus. )Tj /TT1 1 Tf (I highly recommend getting a copy of each of these books, as )Tj 0 -1.16 TD (they will provide a very us)Tj (eful supplement to my lectures and notes. Angrist and Pischke is )Tj 0 -1.14 TD (relatively inexpensive \(~$)Tj (3)Tj (5)Tj (\), and I would strongly suggest that each of you get a copy. The )Tj 0 -1.16 TD (Cameron and Travedi book is great, and it is specifically tailored for p\ eople learning STATA. A)Tj 38.766 0 Td ( )Tj -38.766 -1.14 Td (good strategy might be to order one for each study group \(~$)Tj 24.396 0 Td (75)Tj (\). )Tj ( )Tj -24.396 -1.16 Td ( )Tj ( )Tj 0 -1.14 TD (Angrist and Pischke \(2009\). )Tj /TT2 1 Tf (Mostly Harmless Econometrics: An Empiricist\222s Companion. )Tj /TT0 1 Tf (AP)Tj ( )Tj /TT2 1 Tf 0 -1.16 TD ( )Tj /TT1 1 Tf 0 -1.14 TD (Cameron and Trivedi \(2009\). )Tj /TT2 1 Tf (Microeconometrics Using STATA.)Tj ( )Tj /TT0 1 Tf (CT)Tj (-)Tj (STATA)Tj ( )Tj 0 -1.16 TD ( )Tj /TT1 1 Tf 0 -1.14 TD (Angrist and Pischke)Tj ( )Tj (have a new book )Tj /TT2 1 Tf (Mastering \221Metrics)Tj /TT1 1 Tf (, pitched to an undergraduate crowd )Tj 0 -1.16 TD (that covers many of the same methodologies we study. You may find it use\ ful as well.)Tj 34.521 0 Td ( )Tj -34.521 -1.14 Td ( )Tj /TT0 1 Tf T* (Econometrics Reference Books. )Tj /TT1 1 Tf (I am not going to require you to have any particular one of )Tj 0 -1.14 TD (these. )Tj (I would recommend that you find at least one of the following books that\ you find useful )Tj 0 -1.16 TD (as a reference book. I have tried to include the relevant sections wher\ e possible in the main table )Tj 0 -1.14 TD (below. )Tj ( )Tj 0 -1.16 TD ( )Tj 0 -1.14 TD (Cameron and Trivedi \(2005\). )Tj /TT2 1 Tf (Microeconometrics: Methods )Tj (and Applications)Tj (. )Tj /TT0 1 Tf (CT)Tj ( )Tj 0 -1.16 TD ( )Tj /TT1 1 Tf 0 -1.14 TD (Davidson and MacKinnon \(2004\). )Tj /TT2 1 Tf (Econometric Theory and Methods. )Tj /TT0 1 Tf (DM)Tj ( )Tj 0 -1.16 TD ( )Tj /TT1 1 Tf 0 -1.14 TD (Wooldridge \(2002\). )Tj /TT2 1 Tf (Econometric Analysis of Cross Section and Panel Data. )Tj /TT0 1 Tf (W)Tj ( )Tj 0 -1.16 TD ( )Tj 0 -1.14 TD (Papers. )Tj /TT1 1 Tf (Papers listed in )Tj /TT0 1 Tf (bold)Tj /TT1 1 Tf ( )Tj (are required reading and will be discussed in class duri)Tj (ng one of )Tj 0 -1.16 TD (the meetings scheduled for the topic. Exact dates will be announced as \ we see how we are )Tj 0 -1.14 TD (progressing. The additional papers listed are for reference for the int\ erested student.)Tj 33.765 0 Td ( )Tj -33.765 -1.16 Td ( )Tj T* ( )Tj 0 -1.16 TD ( )Tj ET endstream endobj 15 0 obj <>/ExtGState<>/Font<>/ProcSet[/PDF/Text]>>/Rotate 0/Type/Page>> endobj 16 0 obj <>stream BT /CS0 cs 0 0 0 scn /GS0 gs /TT0 1 Tf 12 0 0 12 72 723.36 Tm (Topics and Readings)Tj ( )Tj 0 -1.14 TD ( )Tj /TT1 1 Tf 0 -1.16 TD (Readings marked with a [*] indicate that i)Tj (f I were you, and I had limited time to read non)Tj 35.739 0 Td (-)Tj -35.739 -1.14 Td (required readings, I would prioritize these.)Tj /TT0 1 Tf 17.022 0 Td ( )Tj /TT1 1 Tf -17.022 -1.16 Td ( )Tj 0 -1.14 TD (Introduction and STATA Basics)Tj /TT0 1 Tf ( )Tj ( )Tj /TT2 1 Tf 4.5 -1.16 Td (o)Tj /C2_0 1 Tf <0001>Tj /TT0 1 Tf 1.5 0 Td (Lecture Notes)Tj ( )Tj /TT2 1 Tf -1.5 -1.14 Td (o)Tj /C2_0 1 Tf <0001>Tj /TT1 1 Tf 1.5 0 Td ([*] CT)Tj (-)Tj (STATA Chapter 1)Tj /TT0 1 Tf ( )Tj -6 -1.16 Td ( )Tj /TT1 1 Tf T* (STATA Programming)Tj /TT0 1 Tf ( )Tj /TT2 1 Tf 4.5 -1.16 Td (o)Tj /C2_0 1 Tf <0001>Tj /TT0 1 Tf 1.5 0 Td (Lecture Notes)Tj ( )Tj /TT2 1 Tf -1.5 -1.14 Td (o)Tj /C2_0 1 Tf <0001>Tj /TT1 1 Tf 1.5 0 Td ([*] CT)Tj (-)Tj (STATA Chapter 1.5)Tj (-)Tj (1.8, 4)Tj /TT0 1 Tf ( )Tj /TT1 1 Tf -6 -1.16 Td ( )Tj T* (STATA Descriptive Stats, )Tj (Figures and Tables)Tj /TT0 1 Tf ( )Tj /TT2 1 Tf 4.5 -1.16 Td (o)Tj /C2_0 1 Tf <0001>Tj /TT0 1 Tf 1.5 0 Td (Lecture Notes)Tj ( )Tj /TT2 1 Tf -1.5 -1.14 Td (o)Tj /C2_0 1 Tf <0001>Tj /TT1 1 Tf 1.5 0 Td ([*] CT)Tj (-)Tj (STATA Chapter 2)Tj /TT0 1 Tf ( )Tj /TT1 1 Tf -6 -1.16 Td ( )Tj T* (STATA Data Management)Tj /TT0 1 Tf ( )Tj /TT2 1 Tf 4.5 -1.16 Td (o)Tj /C2_0 1 Tf <0001>Tj /TT0 1 Tf 1.5 0 Td (Lecture Notes)Tj ( )Tj /TT2 1 Tf -1.5 -1.14 Td (o)Tj /C2_0 1 Tf <0001>Tj /TT1 1 Tf 1.5 0 Td ([*] CT)Tj (-)Tj (STATA Chapter 2)Tj /TT0 1 Tf ( )Tj -6 -1.16 Td ( )Tj /TT1 1 Tf T* (Functional Forms)Tj /TT0 1 Tf ( )Tj /TT2 1 Tf 4.5 -1.16 Td (o)Tj /C2_0 1 Tf <0001>Tj /TT0 1 Tf 1.5 0 Td (Lecture Notes)Tj ( )Tj /TT2 1 Tf -1.5 -1.14 Td (o)Tj /C2_0 1 Tf <0001>Tj /TT1 1 Tf 1.5 0 Td (AP )Tj (\226)Tj ( )Tj (Chapter 3, various parts)Tj /TT0 1 Tf ( )Tj /TT2 1 Tf -1.5 -1.16 Td (o)Tj /C2_0 1 Tf <0001>Tj /TT1 1 Tf 1.5 0 Td (CT)Tj (-)Tj (STATA Chapter 3.3)Tj /TT0 1 Tf ( )Tj /TT2 1 Tf -1.5 -1.14 Td (o)Tj /C2_0 1 Tf <0001>Tj /TT1 1 Tf 1.5 0 Td (CT )Tj (\226)Tj ( )Tj (Chapter 4.1)Tj (-)Tj (4.4)Tj /TT0 1 Tf ( )Tj -6 -1.16 Td ( )Tj /TT1 1 Tf T* (FWL and Multiple Regression)Tj ( )Tj /TT2 1 Tf 4.5 -1.16 Td (o)Tj /C2_0 1 Tf <0001>Tj /TT0 1 Tf 1.5 0 Td (Lecture)Tj ( )Tj (Notes)Tj ( )Tj /TT2 1 Tf -1.5 -1.14 Td (o)Tj /C2_0 1 Tf <0001>Tj 0 0 1 scn /TT1 1 Tf 1.5 0 Td (Lovell\(2008\) A Simple Proof of the FWL Theorem, Journal of Economic )Tj ET 144 321.12 353.04 0.48 re f BT 12 0 0 12 144 309.36 Tm (Education, Vol. 39 No. 1 \(Winter 2008\))Tj 0 0 0 scn /TT0 1 Tf ( )Tj ET 0 0 1 scn 144 307.2 191.52 0.481 re f BT 0 0 0 scn /TT2 1 Tf 12 0 0 12 126.0001 295.68 Tm (o)Tj /C2_0 1 Tf <0001>Tj /TT1 1 Tf 1.5 0 Td (DM pp. 68)Tj (-)Tj (?)Tj /TT0 1 Tf ( )Tj /TT2 1 Tf -1.5 -1.16 Td (o)Tj /C2_0 1 Tf <0001>Tj 0 0 1 scn /TT1 1 Tf 1.5 0 Td (Zax Textbook, Chapter 12, Section 12.4 pp. 26)Tj (-)Tj (35)Tj 0 0 0 scn /TT0 1 Tf ( )Tj ET 0 0 1 scn 144 279.6 241.68 0.48 re f BT 0 0 0 scn /TT1 1 Tf 12 0 0 12 72.0001 268.08 Tm ( )Tj 0 -1.16 TD (The RCT/Treatment Effects)Tj /TT0 1 Tf 11.218 0 Td ( )Tj /TT2 1 Tf -6.718 -1.14 Td (o)Tj /C2_0 1 Tf <0001>Tj /TT0 1 Tf 1.5 0 Td (Lecture Notes)Tj ( )Tj /TT2 1 Tf -1.5 -1.16 Td (o)Tj /C2_0 1 Tf <0001>Tj /TT1 1 Tf 1.5 0 Td ([*] AP )Tj (\226)Tj ( )Tj (Chapter 2)Tj /TT0 1 Tf ( )Tj /TT2 1 Tf -1.5 -1.14 Td (o)Tj /C2_0 1 Tf <0001>Tj /TT1 1 Tf 1.5 0 Td (W )Tj (\226)Tj ( )Tj (Chapter 18)Tj /TT0 1 Tf ( )Tj /TT1 1 Tf -6 -1.16 Td ( )Tj 0 -1.14 TD ( )Tj 0 -1.16 TD (Omitted Variable Bias)Tj /TT0 1 Tf 8.998 0 Td ( )Tj /TT2 1 Tf -4.498 -1.14 Td (o)Tj /C2_0 1 Tf <0001>Tj /TT0 1 Tf 1.5 0 Td (Lecture Notes)Tj ( )Tj /TT2 1 Tf -1.5 -1.16 Td (o)Tj /C2_0 1 Tf <0001>Tj /TT1 1 Tf 1.5 0 Td ([*] AP )Tj (\226)Tj ( )Tj (Chapter 3.2)Tj /TT0 1 Tf ( )Tj /TT2 1 Tf -1.5 -1.14 Td (o)Tj /C2_0 1 Tf <0001>Tj /TT1 1 Tf 1.5 0 Td (DM )Tj (\226)Tj ( )Tj (2.4)Tj (-)Tj (2.5)Tj /TT0 1 Tf ( )Tj /TT2 1 Tf -1.5 -1.16 Td (o)Tj /C2_0 1 Tf <0001>Tj /TT1 1 Tf 1.5 0 Td (W )Tj (\226)Tj ( )Tj (Chapter 4.3)Tj /TT0 1 Tf ( )Tj -6 -1.14 Td ( )Tj /TT1 1 Tf T* (Propensity Score Matching)Tj /TT0 1 Tf ( )Tj /TT2 1 Tf 4.5 -1.14 Td (o)Tj /C2_0 1 Tf <0001>Tj /TT0 1 Tf 1.5 0 Td (Lecture Notes)Tj ( )Tj ET endstream endobj 17 0 obj <>/ExtGState<>/Font<>/ProcSet[/PDF/Text]>>/Rotate 0/Type/Page>> endobj 18 0 obj <>stream BT /CS0 cs 0 0 0 scn /GS0 gs /TT0 1 Tf 12 0 0 12 126 723.36 Tm (o)Tj /C2_0 1 Tf <0001>Tj 0 0 1 scn /TT1 1 Tf 1.5 0 Td (Smith and Todd \(2005\) Does Matching Overcome LaLonde\222s Critique of \ )Tj ET 144 721.2 352.32 0.481 re f BT 12 0 0 12 144 709.68 Tm (Nonexperimental Estimators? )Tj /TT2 1 Tf (Journal of Econometrics)Tj /TT1 1 Tf (, )Tj (Vol 125, No. 1)Tj (-)Tj (2, pp. )Tj ET 144 707.52 373.2 0.481 re f BT 12 0 0 12 144 695.76 Tm (305)Tj (-)Tj (353)Tj 0 0 0 scn /TT3 1 Tf ( )Tj ET 0 0 1 scn 144 693.6 40.08 0.48 re f BT 0 0 0 scn /TT0 1 Tf 12 0 0 12 126 682.08 Tm (o)Tj /C2_0 1 Tf <0001>Tj 0 0 1 scn /TT1 1 Tf 1.5 0 Td (Dehejia \(2005\) Practical Propensity Score Matching: A Reply to Smith a\ nd Todd, )Tj ET 144 679.92 393.36 0.48 re f BT /TT2 1 Tf 12 0 0 12 144 668.16 Tm (Journal of Econometrics)Tj /TT1 1 Tf (, Vol 125, No. 1)Tj (-)Tj (2, pp. 355)Tj (-)Tj (364)Tj 0 0 0 scn /TT3 1 Tf ( )Tj ET 0 0 1 scn 144 666 270.24 0.48 re f BT 0 0 0 scn /TT0 1 Tf 12 0 0 12 126 654.48 Tm (o)Tj /C2_0 1 Tf <0001>Tj 0 0 1 scn /TT1 1 Tf 1.5 0 Td (Smith and Todd \(2005\) Rejoinder)Tj (,)Tj ( )Tj /TT2 1 Tf (Journal of Econometrics)Tj /TT1 1 Tf (, Vol 125, No. 1)Tj (-)Tj (2, pp. )Tj ET 144 652.32 396 0.48 re f BT 12 0 0 12 144 640.56 Tm (365)Tj (-)Tj (375)Tj 0 0 0 scn /TT3 1 Tf ( )Tj ET 0 0 1 scn 144 638.4 40.08 0.481 re f BT 0 0 0 scn /TT0 1 Tf 12 0 0 12 126 626.88 Tm (o)Tj /C2_0 1 Tf <0001>Tj /TT1 1 Tf 1.5 0 Td ([*] CT )Tj (\226)Tj ( )Tj (Chapter 25.4)Tj /TT3 1 Tf ( )Tj /TT0 1 Tf -1.5 -1.16 Td (o)Tj /C2_0 1 Tf <0001>Tj /TT1 1 Tf 1.5 0 Td (W )Tj (\226)Tj ( )Tj (Chapter 18.1)Tj (-)Tj (18.3)Tj /TT3 1 Tf ( )Tj /TT1 1 Tf -6 -1.14 Td ( )Tj 0 -1.16 TD (Panel Data )Tj (\226)Tj ( )Tj (Fixed Effects, etc.)Tj /TT3 1 Tf ( )Tj /TT0 1 Tf 4.5 -1.14 Td (o)Tj /C2_0 1 Tf <0001>Tj /TT3 1 Tf 1.5 0 Td (Lecture Notes)Tj ( )Tj /TT0 1 Tf -1.5 -1.16 Td (o)Tj /C2_0 1 Tf <0001>Tj 0 0 1 scn /TT3 1 Tf 1.5 0 Td (Ashenfelter and Krueger \(1994\) Estimates of the Economic Return to )Tj ET 144 555.12 354.24 0.96 re f BT 12 0 0 12 144 544.08 Tm (Schooling from a New Sample of Twins, )Tj /TT4 1 Tf (American Economic Review)Tj /TT3 1 Tf (, Vol. 84, )Tj ET 144 541.44 392.4 0.96 re f BT 12 0 0 12 144 530.16 Tm (No. 5 \(Dec., 1994\) pp. 1157)Tj (-)Tj (1173)Tj 0 0 0 scn ( )Tj ET 0 0 1 scn 144 527.52 164.4 0.96 re f BT 0 0 0 scn /TT0 1 Tf 12 0 0 12 126 516.48 Tm (o)Tj /C2_0 1 Tf <0001>Tj 0 0 1 scn /TT1 1 Tf 1.5 0 Td (McKinnish \(2008\) Panel Data Models and Transitory Fluctuations in the \ )Tj ET 144 514.32 348.96 0.48 re f BT 12 0 0 12 144 502.56 Tm (Explantory Variable. )Tj /TT2 1 Tf (Advances in Econometrics.)Tj /TT1 1 Tf ( )Tj ( )Tj (Vol. 21 2008.)Tj 0 0 0 scn /TT3 1 Tf ( )Tj ET 0 0 1 scn 144 500.4 308.88 0.48 re f BT 0 0 0 scn /TT0 1 Tf 12 0 0 12 126 488.88 Tm (o)Tj /C2_0 1 Tf <0001>Tj /TT1 1 Tf 1.5 0 Td ([*] AP )Tj (\226)Tj ( )Tj (Chapter 5.1, 5.3, 8.2)Tj /TT3 1 Tf ( )Tj /TT0 1 Tf -1.5 -1.16 Td (o)Tj /C2_0 1 Tf <0001>Tj /TT1 1 Tf 1.5 0 Td ([*] CT)Tj (-)Tj (STATA Chapter 8)Tj /TT3 1 Tf ( )Tj /TT0 1 Tf -1.5 -1.14 Td (o)Tj /C2_0 1 Tf <0001>Tj /TT1 1 Tf 1.5 0 Td (CT )Tj (\226)Tj ( )Tj (Chapter 21)Tj /TT3 1 Tf ( )Tj /TT0 1 Tf -1.5 -1.16 Td (o)Tj /C2_0 1 Tf <0001>Tj /TT1 1 Tf 1.5 0 Td (W )Tj (\226)Tj ( )Tj (Chapter 10)Tj /TT3 1 Tf ( )Tj /TT1 1 Tf -6 -1.14 Td ( )Tj T* (Difference)Tj (-)Tj (in)Tj (-)Tj (Differences)Tj /TT3 1 Tf ( )Tj /TT0 1 Tf 4.5 -1.14 Td (o)Tj /C2_0 1 Tf <0001>Tj /TT3 1 Tf 1.5 0 Td (Lecture )Tj (Notes)Tj ( )Tj /TT0 1 Tf -1.5 -1.16 Td (o)Tj /C2_0 1 Tf <0001>Tj 0 0 1 scn /TT3 1 Tf 1.5 0 Td (Davis \(2004\) The Effect of Health Risk on Housing Values: Evidence fro\ m a )Tj ET 144 389.52 387.36 0.96 re f BT 12 0 0 12 144 378.48 Tm (Cancer Cluster)Tj (.)Tj ( )Tj /TT4 1 Tf (The American Economic Review)Tj /TT3 1 Tf (, Vol. 94, No. 5 \(Dec., 2004\), )Tj ET 144 375.84 387.6 0.96 re f BT 12 0 0 12 144 364.56 Tm (pp. 1693)Tj (-)Tj (1704)Tj 0 0 0 scn ( )Tj ET 0 0 1 scn 144 361.92 71.28 0.96 re f BT 0 0 0 scn /TT0 1 Tf 12 0 0 12 126.0001 350.88 Tm (o)Tj /C2_0 1 Tf <0001>Tj 0 0 1 scn /TT1 1 Tf 1.5 0 Td (Meyer \(1995\). Natural and Quasi)Tj (-)Tj (Experiments in Economics. )Tj /TT2 1 Tf (Journal of )Tj ET 144 348.72 351.6 0.48 re f BT 12 0 0 12 144 336.96 Tm (Business and Economic Statistics.)Tj /TT1 1 Tf ( )Tj (Vol. 13, No. 2 pp. 151)Tj (-)Tj (161)Tj 0 0 0 scn ( )Tj ET 0 0 1 scn 144 334.8 295.92 0.48 re f BT 0 0 0 scn /TT0 1 Tf 12 0 0 12 126.0001 323.28 Tm (o)Tj /C2_0 1 Tf <0001>Tj /TT1 1 Tf 1.5 0 Td ([*] )Tj (AP )Tj (\226)Tj ( )Tj (Chapter)Tj ( )Tj (5.2)Tj ( )Tj /TT0 1 Tf -1.5 -1.16 Td (o)Tj /C2_0 1 Tf <0001>Tj /TT1 1 Tf 1.5 0 Td (CT )Tj (\226)Tj ( )Tj (Chapter 22.6)Tj /TT3 1 Tf ( )Tj /TT0 1 Tf -1.5 -1.14 Td (o)Tj /C2_0 1 Tf <0001>Tj /TT1 1 Tf 1.5 0 Td (W )Tj (\226)Tj ( )Tj (p.130, p. )Tj (284)Tj /TT3 1 Tf ( )Tj -6 -1.16 Td ( )Tj /TT1 1 Tf 0 -1.14 TD (Getting the Standard Errors Right)Tj ( )Tj /TT0 1 Tf 4.5 -1.16 Td (o)Tj /C2_0 1 Tf <0001>Tj /TT3 1 Tf 1.5 0 Td (Lecture Notes)Tj ( )Tj /TT0 1 Tf -1.5 -1.14 Td (o)Tj /C2_0 1 Tf <0001>Tj 0 0 1 scn /TT3 1 Tf 1.5 0 Td (Bertrand et. al. \(2004\) How Much Should We Trust Differences)Tj (-)Tj (in)Tj (-)Tj ET 144 237.84 342.96 0.959 re f BT 12 0 0 12 144 226.56 Tm (Differences Estimates? )Tj /TT4 1 Tf (Quarterly Journal of Economics)Tj /TT3 1 Tf (, V)Tj (ol. 119, No. 1, )Tj ET 144 223.92 364.56 0.96 re f BT 12 0 0 12 144 212.88 Tm (Pages 249)Tj (-)Tj (275)Tj 0 0 0 scn ( )Tj ET 0 0 1 scn 144 210.24 72.24 0.96 re f BT 0 0 0 scn /TT0 1 Tf 12 0 0 12 126 198.96 Tm (o)Tj /C2_0 1 Tf <0001>Tj 0 0 1 scn /TT3 1 Tf 1.5 0 Td (Moulton \(1990\) An Illustration of a Pitfall in Estimating the Effects \ of )Tj ET 144 196.32 356.88 0.96 re f BT 12 0 0 12 144 185.28 Tm (Aggregate Variables on Micro Units, )Tj /TT4 1 Tf (Review of Economics and Statistics)Tj /TT3 1 Tf (, Vol. )Tj ET 144 182.64 392.88 0.96 re f BT 12 0 0 12 144 171.36 Tm (72, No. 2 \(May, 1990\), p)Tj (p. 334)Tj (-)Tj (338)Tj 0 0 0 scn ( )Tj ET 0 0 1 scn 144 168.72 174.24 0.959 re f BT 0 0 0 scn /TT0 1 Tf 12 0 0 12 126.0001 157.68 Tm (o)Tj /C2_0 1 Tf <0001>Tj 0 0 1 scn /TT1 1 Tf 1.5 0 Td (Cameron, Gelbach, and Miller \(2006\) Robust Inference with Multi)Tj (-)Tj (Way )Tj ET 144 155.52 347.28 0.48 re f BT 12 0 0 12 144 143.76 Tm (Clustering, )Tj /TT2 1 Tf (NBER Technical Working Paper)Tj /TT1 1 Tf 17.747 0 Td ( )Tj (No. 327)Tj 0 0 0 scn ( )Tj ET 0 0 1 scn 144 141.6 254.64 0.481 re f BT 0 0 0 scn /TT0 1 Tf 12 0 0 12 126.0001 130.08 Tm (o)Tj /C2_0 1 Tf <0001>Tj 0 0 1 scn /TT1 1 Tf 1.5 0 Td (Cameron, A. Colin and Douglas L. Miller, A Practitioner\222s Guide to Cl\ uster)Tj 30.467 0 Td (-)Tj ET 144 127.92 369.6 0.481 re f BT 12 0 0 12 144 116.16 Tm (Robust Inference, Journal of Human Resources, 50\(2\) March 2015, pp. 31\ 7)Tj (-)Tj (372.)Tj 0 0 0 scn ( )Tj ET 0 0 1 scn 144 114 387.6 0.48 re f BT 0 0 0 scn /TT0 1 Tf 12 0 0 12 126.0001 102.48 Tm (o)Tj /C2_0 1 Tf <0001>Tj /TT1 1 Tf 1.5 0 Td ([*] )Tj (AP )Tj (\226)Tj ( )Tj (Chapter)Tj ( )Tj (8.2)Tj ( )Tj /TT3 1 Tf -1.5 -1.16 Td ( )Tj /TT1 1 Tf -4.5 -1.14 Td (Instrumental Variables)Tj /TT3 1 Tf ( )Tj /TT0 1 Tf 4.5 -1.16 Td (o)Tj /C2_0 1 Tf <0001>Tj /TT3 1 Tf 1.5 0 Td (Lecture Notes)Tj /TT1 1 Tf ( )Tj ET endstream endobj 19 0 obj <>/ExtGState<>/Font<>/ProcSet[/PDF/Text]>>/Rotate 0/Type/Page>> endobj 20 0 obj <>stream BT /CS0 cs 0 0 0 scn /GS0 gs /TT0 1 Tf 12 0 0 12 126 723.36 Tm (o)Tj /C2_0 1 Tf <0001>Tj 0 0 1 scn /TT1 1 Tf 1.5 0 Td (Imbens and Angrist \(1994\) Identification and Estimation of Local Avera\ ge )Tj ET 144 721.2 359.52 0.481 re f BT 12 0 0 12 144 709.68 Tm (Treatment Effects. 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")Tj 0 0 1 scn (Does drinking )Tj ET 462.72 444.72 72.24 0.96 re f BT 12 0 0 12 144 433.68 Tm (impair college performance? 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