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So You Want to Go to Graduate School? Factors That Influence Admissions to Economics PhD Programs

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Title: So You Want to Go to Graduate School? Factors That Influence Admissions to Economics PhD Programs
Language: English
Authors: Jones, Adam, Schuhmann, Peter, Soques, Daniel, Witman, Allison
Source: Journal of Economic Education. 2020 51(2):177-190.
Availability: Routledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals
Peer Reviewed: Y
Page Count: 14
Publication Date: 2020
Document Type: Journal Articles
Reports - Research
Education Level: Higher Education
Postsecondary Education
Descriptors: Economics Education, Doctoral Programs, College Admission, Admission Criteria
DOI: 10.1080/00220485.2020.1731385
ISSN: 0022-0485
Abstract: The authors survey admissions coordinators about the importance of application components in admissions decisions for economics PhD programs. The survey explores the importance of difficult-to-quantify aspects such as a targeted personal statement, strength of letters of recommendation, extracurricular activities, and related work experience. The most important aspects of an application are GPAs in math and economics, letters of recommendation, and GRE quantitative score. The strength of letters of recommendation carries more weight than the prominence of the letter writer. Top-25 programs place a higher value on undergraduate program rank (for students from both domestic and international universities) and strength of letters of recommendation.
Abstractor: As Provided
Entry Date: 2020
Accession Number: EJ1248064
Database: ERIC
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  Value: <anid>AN0142291998;jmd01apr.20;2020Mar19.03:06;v2.2.500</anid> <title id="AN0142291998-1">So you want to go to graduate school? Factors that influence admissions to economics PhD programs </title> <p>The authors survey admissions coordinators about the importance of application components in admissions decisions for economics PhD programs. The survey explores the importance of difficult-to-quantify aspects such as a targeted personal statement, strength of letters of recommendation, extracurricular activities, and related work experience. The most important aspects of an application are GPAs in math and economics, letters of recommendation, and GRE quantitative score. The strength of letters of recommendation carries more weight than the prominence of the letter writer. Top-25 programs place a higher value on undergraduate program rank (for students from both domestic and international universities) and strength of letters of recommendation.</p> <p>Keywords: Economics PhD; graduate admissions; undergraduate education</p> <hd id="AN0142291998-2">Introduction</hd> <p>Faculties are often tasked with advising undergraduate students on how to apply for graduate school and how to maximize their chance of acceptance. Additionally, the number of students needing advising grew as post-baccalaureate degree enrollment increased by 38 percent from 2000 to 2016 and the number of economics PhDs increased at a similar pace (NCES [<reflink idref="bib12" id="ref1">12</reflink>]). At non-PhD-granting institutions, faculty often base their advice on their own personal historical experience. Certainly, students benefit from advisors' anecdotes regarding their graduate school experience. However, inference and suggestions made to students based on a more current and representative sample of graduate school programs can provide additional insight into the admissions process.</p> <p>In this article, we present survey data intended to inform advisors and students as to what graduate programs value when making admissions decisions. Additionally, these data should prove useful when making curriculum decisions at the undergraduate level to better prepare students for graduate studies. For example, adjustments may be necessary given the current direction of economics away from pure theory and toward empirical analysis as suggested by Hamermesh ([<reflink idref="bib8" id="ref2">8</reflink>]) and supported by the finding of Kleven ([<reflink idref="bib9" id="ref3">9</reflink>]) that the fraction of papers mentioning "identification" has grown from virtually none in the early 1990s to nearly half today. Our survey results reflect this change in the profession with programs placing a high importance on math and statistics courses. Indeed, for some graduate programs, success in math and statistics may carry more weight in the admissions process than success in economics courses.</p> <p>We find interesting differences between the preferences of relatively high-ranked programs and low-ranked programs. Our survey results suggest that top programs place a greater emphasis on real analysis than relatively lower-ranked programs, while lower-ranked programs place a greater emphasis on statistics and programming. In addition, the top programs appear to place more emphasis on letter of recommendation strength than lower-ranked programs, which value quantitative GRE scores more highly. This result may reflect a lack of differentiation in quantitative scores between applicants at top programs and an attempt to identify latent differences in student skills. In addition, when considering an applicant's experience outside the classroom, undergraduate research projects are valued more highly than other activities, with top programs placing a greater emphasis on undergraduate research experience than do lower-ranked programs.</p> <p>As the field of economics is moving in a more mathematical and technical direction, those who design curriculum and advise students would be well-served to guide students toward more technical courses and research experiences. Additionally, students should develop relationships and conduct research early in their college careers such that reference letter writers can provide a detailed evaluation of a student's prospects for success in a particular program.</p> <hd id="AN0142291998-3">Literature review</hd> <p>Our study is part of a large and growing body of research on economics PhD program outcomes and is similar to others that use pre-acceptance, ex ante data to identify factors that contribute to a successful application. For example, using data from 48 institutions' 1990 and 1991 applicant pools, Attiyeh and Attiyeh ([<reflink idref="bib2" id="ref4">2</reflink>]) regress acceptance on academic and demographic characteristics of applicants, and find that GRE, GPA, a related undergraduate major, and holding a master's degree have a statistically significant influence on the probability of acceptance. They also find that conditional on other characteristics, being a female or non-Asian minority significantly increases the probability of acceptance into an economics PhD program. Krueger and Wu ([<reflink idref="bib10" id="ref5">10</reflink>]) use data from the 1989 application pool to a top-5 university and find results similar to those of Attiyeh and Attiyeh ([<reflink idref="bib2" id="ref6">2</reflink>]), with the additional finding that prominence of the letter writer is important to admissions committees.[<reflink idref="bib1" id="ref7">1</reflink>] Milkman and Marjadi ([<reflink idref="bib11" id="ref8">11</reflink>]) provide a comprehensive list of math requirements of economics PhD programs through a combination of Web data collection and a survey of PhD admissions coordinators. Although, these papers use rich data, numerous factors related to the academic environment may have changed in the nearly 30 years since these application decisions were made, including program goals and preferences of admissions committees. Additionally, these studies did not include some components of an application, such as the strength of letters of recommendation, personal statements, extracurricular activities, and related work experience. While these elements of an application are more difficult to quantify than measures such as GPA and GRE scores, omitting them may bias empirical results regarding factors that influence the probability of admission.</p> <p>A larger body of research uses post-acceptance data from admitted students to examine characteristics that are predictive of outcomes such as passing qualifying exams, degree completion, time to completion, job market success, and eventual research success.[<reflink idref="bib2" id="ref9">2</reflink>] Admissions committees presumably want to admit students who will become successful graduates; thus, for the purposes of our study, the factors that predict success conditional on admission should be similar to those that predict admission. Consistently, GRE quantitative score, mathematical preparation, undergraduate institution ranking, being foreign-born and research experience predict successful outcomes, although, not in all cases.</p> <p>Many studies of post-admission success are unable to provide insight into how outcomes vary by PhD program rank due to either a small sample size or a sample containing programs from a single tier. Two recent exceptions are Schlauch and Startz ([<reflink idref="bib15" id="ref10">15</reflink>]) and Stock and Siegfried ([<reflink idref="bib22" id="ref11">22</reflink>]), who examine the characteristics that are associated with attending a top-15 PhD program. Schlauch and Startz ([<reflink idref="bib15" id="ref12">15</reflink>]) collect data from the CVs of the 2016–17 job market candidates from the top 50 economics programs. Notably, they show that research experience between completion of an undergraduate degree and beginning a PhD increases the probability of graduating from a highly ranked PhD program. Other findings by Schlauch and Starz ([<reflink idref="bib15" id="ref13">15</reflink>]) are similar to Stock and Siegfried ([<reflink idref="bib22" id="ref14">22</reflink>]), who use a sample of students admitted to 27 PhD programs in 2002 to analyze the characteristics that predict placement into a top-15 program. Both papers find that undergraduate institution ranking and having an undergraduate major in math are predictive of top-15 attendance.</p> <p>Evidence that PhD admissions committees may act strategically based on their program ranking is gained from a qualitative study by Posselt ([<reflink idref="bib14" id="ref15">14</reflink>]), who interviewed admissions committee members at a top-5 program with over 800 applicants. The committee members suggested that the top programs admit "only the best" and often admit the same candidates. One faculty member commented, "I think we have the privilege of taking less risk [on applicants] than other universities of lower ranking" (<reflink idref="bib817" id="ref16">817</reflink>). Based on their assessment, lower-ranked programs do not want to admit applicants with a high probability of acceptance to a top program because those students have a low probability of attending the lower-ranked program. Therefore, programs of different ranks may use different characteristics beyond traditional academic measures to make admissions decisions.</p> <p>Our study contributes to the literature in several ways. First, in addition to quantifiable characteristics examined in previous studies, we capture less quantifiable admission variables such as a targeted personal statement and strength of letters of recommendation. These additional variables have remained relatively unexplored in the literature. Second, we have a broad sample representing the spectrum of economics PhD-granting programs, allowing for an analysis of differences by program ranking. We also conduct a more detailed examination of economics classes than has previously been presented in the literature. Finally, we examine the importance of emerging factors for PhD program admissions that have not yet been explored, including programming languages, undergraduate research experience, and extracurricular activities. The examination of these emerging factors is necessitated by the increasing emphasis on quantitative research in the field. The results from this study are intended to inform faculty advising students on how to prepare for and improve their chance of acceptance to a PhD program in economics. In addition, we hope to provide insights into how undergraduate programs can properly prepare their students for graduate school.</p> <hd id="AN0142291998-4">Data</hd> <p>We conducted an online survey of individuals familiar with the admissions process at economics PhD programs in the United States.[<reflink idref="bib3" id="ref17">3</reflink>] The survey was designed and pre-tested incorporating suggestions and feedback from several current and former graduate admissions coordinators as well as undergraduate coordinators in order to generate questions that would account for a variety of admissions processes across universities without overburdening respondents.</p> <p>Prior to sending the survey, we contacted all PhD programs in the United States to identify the individual most knowledgeable about their respective admissions process. The survey was subsequently emailed to the target individual at 132 programs in May 2018, which was timed to coincide with the completion of the admissions and recruiting process at most PhD programs. Respondents may have been unwilling to reveal information about admissions preferences if they could be identified; therefore, all data were collected anonymously in hopes of increasing the response rate and reducing response bias. Two weeks after the initial survey request, a follow-up reminder was sent. Sixty-nine responses to the survey were collected, yielding a response rate of 52 percent. Individual responses were included in the sample if the respondent completed the survey, although not all respondents completed every question. The sample does not include respondents who terminated the survey prior to completion.</p> <p>Survey questions covered background information about the respondent and the program, including the amount of experience the respondent had with the admissions process, self-assessed program ranking,[<reflink idref="bib4" id="ref18">4</reflink>] minimum and average GRE, GPA, TOEFL, acceptance rate, the typical cohort size, and the typical number of PhDs awarded per year. Next, we asked respondents about the characteristics that the literature shows to be influential in admissions decisions including undergraduate program rank, graduate program rank, post-baccalaureate work experience, GRE scores, GPA, a directed statement of purpose, letters of reference, prominence of reference letter writers, and mathematics major/minor. To assess whether programs consider diversity in admissions decisions, we asked whether U.S. citizenship, gender, race, and geographic location of the student were important for admissions and funding decisions. A 5-point Likert scale was used to rate characteristics to capture quantitative results versus capturing some of the more nuanced details of the admissions process through a free-response format. Respondents rated each characteristic as (<reflink idref="bib1" id="ref19">1</reflink>) not at all important, (<reflink idref="bib2" id="ref20">2</reflink>) slightly important, (<reflink idref="bib3" id="ref21">3</reflink>) moderately important, (<reflink idref="bib4" id="ref22">4</reflink>) very important, or (<reflink idref="bib5" id="ref23">5</reflink>) extremely important.[<reflink idref="bib5" id="ref24">5</reflink>]</p> <p>Advising students often requires giving specific advice about what classes to take and whether to specialize in a certain programming language in preparation for applying to a PhD program. Therefore, we asked respondents to rate economics and math classes in terms of their importance. To assess whether programming experience in a specific language is important, respondents also rated most of the programming languages used across economics. To our knowledge, previous research has not considered programming experience. Undergraduate programs may find this information useful as to which programming language(s) to teach in an econometrics sequence.</p> <p>We also wanted to obtain ratings on student activities beyond the traditional academic preparations. High-achieving students often complete extracurricular activities, yet the value of these is unclear in terms of graduate program admission. Respondents were, therefore, asked to rate the importance of undergraduate research experience (completed a paper, presented at a conference, worked as a research assistant), academic extracurricular activities (Fed challenge, Fiscal challenge, etc.), working as a tutor or teaching assistant, related internships, and club leadership. With the exception of undergraduate research experience, these characteristics have not been examined in previous research.</p> <p>While the survey used a 5-point response scale of "not," "slightly," "moderately," "very," or "extremely important," for ease of presentation and interpretation we aggregate to three levels, combining the lowest two responses as "not important" and the highest two responses as "very important." We test for differences in importance rating by program rank using a proportions test. That is, we test for differences in the percentage of respondents who rated a characteristic very or extremely important between programs whose self-reported ranks are in the top 25 (henceforth, T25) and programs whose self-reported rank is 50 or lower (50+).[<reflink idref="bib6" id="ref25">6</reflink>]</p> <p>Survey data in general are subject to several limitations including selection bias and the tendency of respondents to systematically report desired rather than factual responses. The anonymous and voluntary nature of the survey generated three limitations specific to this project. First, anonymously collected responses require that program rank is self-reported rather than collected from an impartial source. Although this question lends itself to potential self-reporting bias, graduate admissions coordinators have little incentive to misrepresent the rank of their program in an anonymous survey. Further, we have no reason to believe that such misrepresentation would be systematic, such that a particular category of program consistently over- or under-reports their ranking. Second, responding to each question was voluntary, allowing respondents to opt out of individual questions. Comparisons of question responses are therefore subject to differences in statistical power created by different response rates.[<reflink idref="bib7" id="ref26">7</reflink>] Lastly, there can be sample selection bias because not all programs opted to respond to the survey. If programs opted out of the survey for a systematic reason, this could potentially bias our results by placing more weight on the characteristics and ratings of programs included in the sample.</p> <hd id="AN0142291998-5">Results</hd> <p>Table 1 presents the sample characteristics. Of the 132 requests, 69 program coordinators answered the survey. The sample includes programs from across the ranking continuum, including six self-reported top-10 programs, 33 top-50 programs, 34 programs ranked outside the top 50, and two programs that declined to provide rank. Higher-ranked programs in our sample tend to have lower acceptance rates, larger entering class cohorts, and grant more PhDs per year. The acceptance rate ranges from 1 to 99 percent. The average cohort size is 12 students, with nine PhDs awarded per year. In total, programs reported 645 PhDs awarded per year, which is approximately 52 percent of the economics PhDs awarded in 2016 (NSF [<reflink idref="bib13" id="ref27">13</reflink>]).</p> <p>Table 1. Sample characteristics.</p> <p> <ephtml> <table><thead><tr><td /><td /><td>Program rank</td></tr><tr><td /><td>All (Standard deviation) [Range]</td><td>1 − 10</td><td>11 − 25</td><td>26 − 50</td><td>51 − 100</td><td>100+</td></tr></thead><tbody valign="top"><tr><td>Acceptance rate</td><td>25.96</td><td>8.33</td><td>11.38</td><td>19.37</td><td>30.42</td><td>54.88</td></tr><tr><td /><td>(20.92)</td><td>(4.72)</td><td>(3.02)</td><td>(13.66)</td><td>(17.76)</td><td>(28.94)</td></tr><tr><td /><td>[1, 99]</td><td>[1, 13]</td><td>[5, 15]</td><td>[3, 55]</td><td>[10, 72]</td><td>[10, 99]</td></tr><tr><td>Entering cohort size</td><td>12.02</td><td>22.33</td><td>19.00</td><td>12.78</td><td>8.24</td><td>7.38</td></tr><tr><td /><td>(6.44)</td><td>(2.88)</td><td>(4.81)</td><td>(4.44)</td><td>(4.25)</td><td>(4.00)</td></tr><tr><td /><td>[0, 25]</td><td>[18, 25]</td><td>[12, 25]</td><td>[6, 23]</td><td>[0, 16]</td><td>[2, 14]</td></tr><tr><td>PhDs awarded per year</td><td>9.34</td><td>18.67</td><td>15.25</td><td>8.88</td><td>5.40</td><td>3.75</td></tr><tr><td /><td>(8.21)</td><td>(2.80)</td><td>(5.04)</td><td>(3.50)</td><td>(2.71)</td><td>(1.39)</td></tr><tr><td /><td>[0, 57]</td><td>[16, 24]</td><td>[8, 22]</td><td>[4, 15]</td><td>[0, 10]</td><td>[1, 5]</td></tr><tr><td><italic>N</italic></td><td>69</td><td>6</td><td>8</td><td>19</td><td>26</td><td>8</td></tr></tbody></table> </ephtml> </p> <p>1 <emph>Note:</emph> Table contains characteristics of survey sample including the mean, standard deviation in parentheses, and range in brackets. Two programs declined to provide rank.</p> <p>We present survey results using figures with supporting tables presented in Online Appendix B (Supporting Information). In each figure, characteristics are sorted by the percent of programs responding that the item is very or extremely important (henceforth referred to as "very important"), illustrating which characteristics are most important in application decisions. The right side of each figure includes a column presenting the difference between the proportion of T25 programs indicating a characteristic is at least very important and the proportion of programs ranked 50+ that indicated the characteristic is at least very important. A positive number indicates that more T25 programs place high importance on the respective factor. Using a test for equality of proportions across the two subgroups, we indicate when T25 programs place relatively more or less weight on a characteristic than 50+ programs.</p> <p>Figure 1 summarizes the importance of an applicant's undergraduate and master's program rank in the admission process. Program rank is analyzed separately for American students who attended American undergraduate and master's programs, foreign students attending American undergraduate and master's programs, and foreign students attending foreign undergraduate and master's programs. PhD programs appear to weigh an applicant's domestic program ranking in a similar way for both domestic and international students (30% and 24% reported very important, respectively). However, for students matriculating from international programs, rank is more highly valued in admissions decisions with 54 percent of respondents saying undergraduate program rank is very important and 44 percent of respondents reporting graduate program rank as very important. Using a test for equality of proportions across the two subgroups, we find that T25 programs place relatively more weight on domestic undergraduate program rank for both domestic and international students than 50+ programs.</p> <p>Graph: Figure 1. Importance of program rank. Note: Figure presents results of graduate admissions coordinator survey. The percentage of programs responding very or extremely important (very), slightly or moderately important (moderately), or not important, is shown for each characteristic. On the right side of the figure, the difference in the proportion of top-25 versus 50+ ranked programs responding a characteristic is very important is provided, with a test of proportions for significance. *p <.10; **p <.05; ***p <.01</p> <p>The importance of applicants' demographic characteristics is shown in figure 2. A majority of respondents said gender and race were at least moderately important in admissions decisions. Nearly 15 percent of respondents said that gender and 12 percent of respondents said that race was very important. Additionally, we find no significant difference between T25 and 50+ programs in the consideration of gender and race in acceptance decisions. Other demographic characteristics such as U.S. citizenship and in-state residency status do not appear to be as important to programs' acceptance decisions.[<reflink idref="bib8" id="ref28">8</reflink>]</p> <p>Graph: Figure 2. Importance of student demographics. Note: Figure presents results of graduate admissions coordinator survey. The percentage of programs responding very or extremely important (very), slightly or moderately important (moderately), or not important, is shown for each characteristic. On the right side of the figure, the difference in the proportion of top-25 versus 50+ ranked programs responding a characteristic is very important is provided, with a test of proportions for significance. *p <.10; **p <.05; ***p <.01</p> <p>Figures 1 and 2 present characteristics that are largely predetermined and, therefore, are difficult for applicants to modify on short notice. For example, applicants may be able to relocate and, after a period of time, qualify as "in-state" or change citizenship, but there is typically a substantial lag between the decision and reclassification. Thus, we next examine application components that students may be able to influence prior to applying for graduate school. Figure 3 displays the importance of specific economics courses for admission.[<reflink idref="bib9" id="ref29">9</reflink>] Core economics courses at both the principles and intermediate level are highly important in acceptance decisions, with more than 60 percent of respondents placing a very important rating on intermediate-level coursework and econometrics. Field-specific courses are relatively less important. In general, the most important electives include advanced macroeconomics, environmental economics, and health economics. The least important courses included finance and money and banking. However, we should note that these are aggregate results for the sample.</p> <p>Graph: Figure 3. Importance of economics courses. Note: Figure presents results of graduate admissions coordinator survey. The percentage of programs responding very or extremely important (very), slightly or moderately important (moderately), or not important, is shown for each course. On the right side of the figure, the difference in the proportion of top-25 versus 50+ ranked programs responding a characteristic is very important is provided, with a test of proportions for significance. *p <.10; **p <.05; ***p <.01</p> <p>The importance of specific math courses is presented in figure 4. Consistent with all previous research, math is highly valued in admissions decisions. The most important math courses include the calculus sequence (Calculus I, II, and III), linear algebra, and statistics, which 88, 86, 68, 76, and 68 percent of respondents rated as very important, respectively. The traditional advice that students take more math is, therefore, strongly supported by these results. Statistics is more highly valued by 50+ programs while real analysis is more highly valued by T25 programs.</p> <p>Graph: Figure 4. Importance of math courses. Note: Figure presents results of graduate admissions coordinator survey. The percentage of programs responding very or extremely important (very), slightly or moderately important (moderately), or not important, is shown for each course. On the right side of the figure, the difference in the proportion of top-25 versus 50+ ranked programs responding a characteristic is very important is provided, with a test of proportions for significance. *p <.10; **p <.05; ***p <.01</p> <p>Figure 5 shows the importance of the application characteristics typically described in the literature. More than 80 percent of programs rate math and economics GPA as very or extremely important. More programs indicated math GPA to be very important, 87 percent, than economics GPA, 81 percent. Approximately 10 percent of programs indicated an applicant's math GPA is very important and did not indicate that an applicant's economics GPA is very important. The strength of an applicant's letter(s) of recommendation is important relative to many other characteristics, and significantly more so for T25 programs than 50+ programs. However, the prominence of the letter writer(s) ranks at the bottom of the listed characteristics. The quantitative portion of the GRE is important to all programs, but 50+ programs place a significantly higher degree of importance on it than T25 programs do. One potential explanation for this is that T25 programs choose only students with very high GRE scores, so the quantitative GRE contains less information for them compared to 50+ programs. An applicant's verbal GRE score is relatively less important, but only seven programs (10% of the sample) classified it as "not important."</p> <p>Graph: Figure 5. Importance of application characteristics. Note: Figure presents results of graduate admissions coordinator survey. The percentage of programs responding very or extremely important (very), slightly or moderately important (moderately), or not important, is shown for each item. On the right side of the figure, the difference in the proportion of top-25 versus 50+ ranked programs responding a characteristic is very important is provided, with a test of proportions for significance. *p <.10; **p <.05; ***p <.01</p> <p>The importance of extracurricular activities in admission decisions is shown in figure 6. While not all these activities are "extra" at all institutions, they are activities that are likely to be outside the standard course catalog at many undergraduate institutions. For example, competitions such as the Fed Challenge can include course credit but are optional at most institutions and are not traditional coursework. Activities related to research (e.g., writing a research paper, acting as a research assistant, or presenting at a conference) are the most important. Nearly 60 percent of respondents said club leadership roles were not important. We find no significant difference in these rankings between T25 and 50+ programs; however, the signs on the differences, while not statistically significant, may indicate that higher-ranked programs value research activities while lower-ranked programs value tutoring and other academic extracurricular activities.[<reflink idref="bib10" id="ref30">10</reflink>] These differential admissions preferences align with graduates of top programs having more research-focused career paths and graduates of lower-ranked programs focusing more on teaching in their career and possibly during their time in graduate school.</p> <p>Graph: Figure 6. Importance of extracurricular activities. Note: Figure presents results of graduate admissions coordinator survey. The percentage of programs responding very or extremely important (very), slightly or moderately important (moderately), or not important, is shown for each item. On the right side of the figure, the difference in the proportion of top-25 versus 50+ ranked programs responding a characteristic is very important is provided, with a test of proportions for significance. *p <.10; **p <.05; ***p <.01</p> <p>One relatively recent development in the field is the growth in empirical analysis (Angrist et al. [<reflink idref="bib1" id="ref31">1</reflink>]; Hamermesh [<reflink idref="bib8" id="ref32">8</reflink>]), which points to the importance of statistical software, data processing, and programming. Programming abilities secured prior to entering the PhD program may signal skills and experiences that predict success in a PhD program such as research ability, data analysis skills, and analytical and logical thinking. From the perspective of faculty at undergraduate institutions, knowledge of preferred programming languages may be useful for curriculum design. We explore how program coordinators value programming experience in figure 7. Overall, programming experience is not important relative to the other admission factors discussed above, with 18 percent of respondents saying that any experience is very or extremely important. For instructors choosing which language to teach, it appears that the most valued languages are MATLAB, Stata, SAS, and R. However, no software appears significantly more important than other software packages. Yet, while there were no significant differences between T25 and 50+ programs for a specific software language, lower-ranked programs were more likely to indicate that one or more of the languages is very important.</p> <p>Graph: Figure 7. Importance of programming skills. Note: Figure presents results of graduate admissions coordinator survey. The percentage of programs responding very or extremely important (very), slightly or moderately important (moderately), or not important, is shown for each programming language. On the right side of the figure, the difference in the proportion of top-25 versus 50+ ranked programs responding a characteristic is very important is provided, with a test of proportions for significance. *p <.10; **p <.05; ***p <.01</p> <p>Figure 8 displays the importance of different post-baccalaureate options. A master's degree is important, and much more so if it is in a quantitative field. Almost half of the respondents classified a nonquantitative master's as "not important." Programs appear to be lukewarm about work experience in general, but preferences may depend on the type of work that was not captured in this survey. For example, work experience that includes research duties (e.g., a research assistantship at a Federal Reserve Bank) may be valued differently than work experience unrelated to research or economics.</p> <p>Graph: Figure 8. Importance of post-baccalaureate experience. Note: Figure presents results of graduate admissions coordinator survey. The percentage of programs responding very or extremely important (very), slightly or moderately important (moderately), or not important, is shown for each item. On the right side of the figure, the difference in the proportion of top-25 versus 50+ ranked programs responding a characteristic is very important is provided, with a test of proportions for significance. *p <.10; **p <.05; ***p <.01</p> <hd id="AN0142291998-6">Discussion</hd> <p>The results of our survey should prove beneficial to students and advisers faced with decisions about course selection, time allocation, and PhD program applications. A number of our findings align with the standard recommendations made to students. GPA, particularly in mathematics, and quantitative GRE scores are important factors of the admission process. Importantly, while we find that the quantitative portion of the GRE is important to all programs, 50+ programs place a significantly higher degree of importance on this measure than T25 programs. One potential explanation for this is that T25 programs consider only applicants with very high quantitative GRE scores and, therefore, there is less variation in this characteristic among applicants at the top programs. As a result, higher-ranked programs often must rely on alternative (and more subjective) characteristics to differentiate applicants with similar GPA and quantitative GRE score profiles. However, GPA and quantitative GRE scores are more heavily used in admission decisions by lower-ranked programs because a higher degree of variation offers more distinguishing information.</p> <p>With regard to PhD program ranking, our finding that higher-ranked programs admit larger class sizes but have lower acceptance rates suggests a high degree of competition for admission to these programs. This is not surprising but serves as an important reminder that students who may not have the undergraduate pedigree to support admission to top programs should also apply to mid- and lower-ranked programs.</p> <p>We find that for students attending international undergraduate or master's programs, program rank is critical. Stock and Siegfried ([<reflink idref="bib22" id="ref33">22</reflink>]) and Schlauch and Startz ([<reflink idref="bib15" id="ref34">15</reflink>]) find that a master's degree is predictive of top program attendance for foreign but not domestic students. Additionally, the caliber of the master's program rather than simply having the master's is important. Students from outside the United States who wish to attend American economics PhD programs should therefore understand the importance of program rank. As many students do not decide to attend graduate programs until fully immersed in an undergraduate experience, it may be advisable for strong students to consider the possibility of transferring to higher-ranked undergraduate programs or entering a master's program prior to applying for their PhD. While such actions are likely to be costly, our findings suggest that they will improve the chances of PhD program admission.</p> <p>Understanding the importance of different courses in the admissions decision can be useful for students faced with time and/or credit hour constraints. With regard to economics courses, our results suggest that success in the core economics courses (principles, intermediate, and econometrics) carries the most weight in the admissions process. An important caveat is that specific field courses may indeed be important for particular programs with research focus in those areas of study. With regard to mathematics, it appears that courses in the calculus sequence are the most important, followed by linear algebra and statistics. These findings align with Milkman and Marjadi's ([<reflink idref="bib11" id="ref35">11</reflink>]) list of required and preferred classes for economics PhD programs. It may be the case that students with plans to attend a PhD program would be better served taking more of these courses than field courses in economics. Importantly, higher-ranked programs value different math courses than lower-ranked programs, which tend to place a higher emphasis on statistics courses. Therefore, students should consider the tier of PhD program they are targeting when selecting which math courses to take. In particular, directors at top graduate programs stressed the importance of real analysis in understanding proofs and succeeding in graduate theory courses.</p> <p>Extracurricular and work experience seem unimportant to PhD program admissions unless the work is directly related to research or economics. The related finding that club leadership roles do not appear to carry weight in PhD program admissions runs counter to the common idea that students should pursue leadership roles as undergraduates to illustrate well-rounded resumes. Students seeking admission to economics PhD programs would therefore be advised to forgo onerous work or service roles and instead seek out research experiences or, when possible, forgo such efforts in favor of time dedicated to academic success.</p> <p>We find that the quality of letters of recommendation appears to carry more weight than the prominence of the letter writers. When considering the tradeoff between a letter from a faculty member who can provide details regarding the student's abilities and experiences versus a prominent faculty member with less knowledge of the student, applicants would be advised to request letters from faculty who know them well enough to provide a quality recommendation. Combining this result with our findings related to course and research experience suggests that students should request letters of recommendation from faculty who can provide strong recommendations regarding success in core economics courses, mathematics courses and/or aptitude for research, regardless of the prominence of the individual faculty member. However, we should note that several graduate studies directors mentioned in discussions outside of the survey that they preferred letters from tenured or tenure-track faculty (i.e., active research faculty) as opposed to lecturers because the latter may not be able to assess a student's research proficiency.</p> <p>U.S. citizenship and in-state status do not appear to be significant determinants of admissions to PhD programs in economics. Demographic factors such as gender and race do appear to carry some weight in admissions decisions. This result may reflect diversity efforts made in response to disproportionate under-representation of females and minorities in economics (Bayer and Rouse [<reflink idref="bib3" id="ref36">3</reflink>]). We do not find significant differences in the importance of these factors between top-ranked and lower-ranked programs. It is important to note the true role of attributes such as race, gender and nationality in admissions decisions is difficult to assess. When faced with sensitive issues related to equality and inclusiveness, survey respondents may answer questions inaccurately due to social desirability bias or may answer based on how they believe they should answer, potentially masking the true importance of these characteristics.</p> <p>One of the more salient conclusions of this study is that the probability of successful admission to top PhD programs is enhanced by students differentiating themselves from a large field of high-achieving applicants. This differentiation can be achieved through a variety of avenues that serve as additional signals of analytical skills and passion for economics in general, including strong letters of recommendation, early research experience, and success in higher-level mathematics courses.</p> <hd id="AN0142291998-7">Acknowledgments</hd> <p>The authors thank KimMarie McGoldrick for the list of economics PhD programs and helpful comments on the article. The authors also thank Gail Hoyt for organizing and chairing the AEA session centered on our paper and the panelists for that session: Gautam Gowrisankaran, Navin Kartik, Martin Boileau, Wojciech Olszewski, Daniele Paserman, and Marcus Berliant. Finally, the authors thank the participants at UNCW's 2018 Economic Teaching Workshop, SEA 2018, and AEA 2019.</p> <ref id="AN0142291998-8"> <title> Footnotes </title> <blist> <bibl id="bib1" idref="ref7" type="bt">1</bibl> <bibtext> Becker, Rouse, and Chen ([4]) focus on a narrower aspect of admission and evaluate the impact of the American Economic Association's (AEA) summer program for minorities. They find that participants were more than 45 percentage points more likely to apply and 40 percentage points more likely to attend a PhD program in economics.</bibtext> </blist> <blist> <bibl id="bib2" idref="ref4" type="bt">2</bibl> <bibtext> See Conley and Önder ([5]), Grove and Wu ([6]), Grove, Dutkowsky, and Grodner ([7]), Schlauch and Startz ([15]), Siegfried and Stock ([16]), Stock and Hansen ([19]), Stock and Siegfried ([20], [21], [22]), Stock, Finegan, and Siegfried ([17], [18]), Stock, Siegfried, and Finegan ([23]), van Ours and Ridder ([24]), among others.</bibtext> </blist> <blist> <bibl id="bib3" idref="ref17" type="bt">3</bibl> <bibtext> See Online Appendix A (https://doi.org/10.1080/00220485.2020.1731385) for the full survey questions.</bibtext> </blist> <blist> <bibl id="bib4" idref="ref18" type="bt">4</bibl> <bibtext> Note that we asked admission coordinators to self-describe their PhD program rank rather than their institutional rank (see Q4.11 in Online Appendix A [ https://doi.org/10.1080/00220485.2020.1731385]).</bibtext> </blist> <blist> <bibl id="bib5" idref="ref23" type="bt">5</bibl> <bibtext> Although, a 5-point rating scale was used to collect survey data, the 5-point scale was collapsed to a less granular 3-point scale during the analysis. Results were qualitatively similar, suggesting imperceptible differences between "slightly important" and "moderately important" and between "very important" and "extremely important." Categories were combined to reduce the number of empty cells occurring when no program indicated a characteristic was extremely, very, moderately, slightly, or not important. Additionally, the combined Likert scale increased power for statistical tests of proportions for subsamples of programs.</bibtext> </blist> <blist> <bibl id="bib6" idref="ref25" type="bt">6</bibl> <bibtext> We also conducted the proportions tests comparing T50 and 50+ schools. The results are largely similar. The following important, statistically significant differences emerge: when comparing T50 and 50+ schools, (1) U.S. citizenship is less important to T50 schools, (2) rank of graduate program attended by an international student is more important to T50 schools, (3) more T50 schools rate verbal GRE score as moderately important, and (4) fewer T50 schools rated SAS and R as very important programming languages.</bibtext> </blist> <blist> <bibl id="bib7" idref="ref26" type="bt">7</bibl> <bibtext> Questions had an average response rate of 79 percent. Ninety-five percent of questions had a response rate higher than 50 percent.</bibtext> </blist> <blist> <bibl id="bib8" idref="ref2" type="bt">8</bibl> <bibtext> Online Appendix B Table 2 (https://doi.org/10.1080/00220485.2020.1731385) contains proportions tests comparing the percentage of T25 and 50+ programs that said a characteristic was not important or moderately important. T25 programs are less likely to rank gender as not important and more likely to rank it as moderately important in admissions decisions.</bibtext> </blist> <blist> <bibl id="bib9" idref="ref3" type="bt">9</bibl> <bibtext> The survey question asked respondents only about the importance of a student having taken the course and not how performance in the course factored into the admission decision.</bibtext> </blist> <blist> <bibtext> <emph>p</emph> values for all differences are presented in the Online Appendix (https://doi.org/10.1080/00220485.2020.1731385). The Appendix also includes a comparison of the proportion of T25 and 50+ programs stating that a characteristic was not important. T25 schools were less likely to say that prominence of the letter writer, being a tutor, and programming skills were not important.</bibtext> </blist> <blist> <bibtext> Supplemental data for this article is available online at https://doi.org/10.1080/00220485.2020.1731385</bibtext> </blist> </ref> <ref id="AN0142291998-9"> <title> References </title> <blist> <bibtext> Angrist, J., P. Azoulay, G. Ellison, R. Hill, and S. F. Lu. 2017. Economic research evolves: Fields and styles. American Economic Review 107 (5): 293 – 97. doi: 10.1257/aer.p20171117.</bibtext> </blist> <blist> <bibtext> Attiyeh, G., and R. Attiyeh. 1997. Testing for bias in graduate school admissions. Journal of Human Resources 32 (3): 524 – 48. doi: 10.2307/146182.</bibtext> </blist> <blist> <bibtext> Bayer, A., and C. Rouse. 2016. Diversity in the economics profession: A new attack on an old problem. Journal of Economic Perspectives 30 (4): 221 – 42. doi: 10.1257/jep.30.4.221.</bibtext> </blist> <blist> <bibtext> Becker, C., C. Rouse, and M. Chen. 2016. Can a summer make a difference? The impact of the American Economic Association Summer Program on minority student outcomes. Economics of Education Review 53 (August): 46 – 71. doi: 10.1016/j.econedurev.2016.03.009.</bibtext> </blist> <blist> <bibtext> Conley, J. P., and A. S. Önder. 2014. The research productivity of new PhDs in economics: The surprisingly high non-success of the successful. Journal of Economic Perspectives 28 (3): 205 – 16. doi: 10.1257/jep.28.3.205.</bibtext> </blist> <blist> <bibtext> Grove, W., D. Dutkowsky, and A. Grodner. 2007. Survive then thrive: Determinants of success in the economics PhD program. Economic Inquiry 45 (4): 864 – 71. doi: 10.1111/j.1465-7295.2007.00041.x.</bibtext> </blist> <blist> <bibtext> Grove, W., and S. Wu. 2007. The search for economics talent: Doctoral completion and research productivity. American Economic Review 97 (2): 506 – 11. doi: 10.1257/aer.97.2.506.</bibtext> </blist> <blist> <bibtext> Hamermesh, D. 2013. Six decades of top economics publishing: Who and how? Journal of Economic Literature 51 (1): 162 – 72. doi: 10.1257/jel.51.1.162.</bibtext> </blist> <blist> <bibtext> Kleven, H. 2018. Language trends in public economics. Slides. Princeton, NJ : Princeton University.</bibtext> </blist> <blist> <bibtext> Krueger, A., and S. Wu. 2000. Forecasting job placements of economics graduate students. Journal of Economic Education 31 (1): 81 – 94. doi: 10.1080/00220480009596765.</bibtext> </blist> <blist> <bibtext> Milkman, M., and R. Marjadi. 2017. Undergraduate mathematics courses required and recommended for admission to economics PhD programs in the United States. The American Economist 62 (1): 118 – 25. doi: 10.1177/0569434516672777.</bibtext> </blist> <blist> <bibtext> National Center for Education Statistics (NCES). 2019. Postbaccalaureate enrollment. Washington, DC : U.S. Department of Education, Institute of Education Sciences, NCES. https://nces.ed.gov/programs/coe/indicator%5fchb.asp (accessed September 12, 2019).</bibtext> </blist> <blist> <bibtext> National Science Foundation (NSF). 2017. 2016 doctorate recipients from U.S. universities. Science & Engineering Doctorates (Web site). https://<ulink href="http://www.nsf.gov/statistics/2018/nsf18304/">www.nsf.gov/statistics/2018/nsf18304/</ulink> (accessed September 12, 2019).</bibtext> </blist> <blist> <bibtext> Posselt, J. 2015. Disciplinary logics in doctoral admission: Understanding patterns of faculty evaluation. Journal of Higher Education 86 (6): 807 – 33. doi: 10.1353/jhe.2015.0030.</bibtext> </blist> <blist> <bibtext> Schlauch, G., and R. Startz. 2018. The path to an economics PhD. Economics Bulletin 38 (4): 1864 – 76.</bibtext> </blist> <blist> <bibtext> Siegfried, J., and W. Stock. 2004. The market for new PhD economists in 2002. American Economic Review 94 (2): 272 – 85. doi: 10.1257/0002828041301597.</bibtext> </blist> <blist> <bibtext> Stock, W., T. Finegan, and J. Siegfried. 2009a. Can you earn a PhD in economics in five years? Economics of Education Review 28 (5): 523 – 37. doi: 10.1016/j.econedurev.2009.04.001.</bibtext> </blist> <blist> <bibtext> Stock, W., T. Finegan, and J. Siegfried. 2009b. Completing an economics PhD in five years. American Economic Review 99 (2): 624 – 29.</bibtext> </blist> <blist> <bibtext> Stock, W., and W. Hansen. 2004. PhD program learning and job demands: How close is the match? American Economic Review 94 (2): 266 – 71. doi: 10.1257/0002828041302343.</bibtext> </blist> <blist> <bibtext> Stock, W., and J. Siegfried. 2006. Time-to-degree for the economics PhD class of 2001–2002. American Economic Review 96 (2): 467 – 74. doi: 10.1257/000282806777212134.</bibtext> </blist> <blist> <bibtext> Stock, W., and J. Siegfried. 2014. Fifteen years of research on graduate education in economics: What have we learned? Journal of Economic Education 45 (4): 287 – 303.</bibtext> </blist> <blist> <bibtext> Stock, W., and J. Siegfried. 2015. The undergraduate origins of PhD economists revisited. Journal of Economic Education 46 (2): 150 – 65.</bibtext> </blist> <blist> <bibtext> Stock, W., J. Siegfried, and T. Finegan. 2011. Completion rates and time-to-degree in economics PhD programs. American Economic Review Papers & Proceedings 101 (3): 176 – 88. doi: 10.1257/aer.101.3.176.</bibtext> </blist> <blist> <bibtext> van Ours, J. C., and G. Ridder. 2003. Fast track or failure: A study of the graduation and dropout rates of PhD students in economics. Economics of Education Review 22 (2): 157 – 66. doi: 10.1016/S0272-7757(02)00029-8.</bibtext> </blist> </ref> <aug> <p>By Adam Jones; Peter Schuhmann; Daniel Soques and Allison Witman</p> <p>Reported by Author; Author; Author; Author</p> </aug> <nolink nlid="nl1" bibid="bib12" firstref="ref1"></nolink> <nolink nlid="nl2" bibid="bib10" firstref="ref5"></nolink> <nolink nlid="nl3" bibid="bib11" firstref="ref8"></nolink> <nolink nlid="nl4" bibid="bib15" firstref="ref10"></nolink> <nolink nlid="nl5" bibid="bib22" firstref="ref11"></nolink> <nolink nlid="nl6" bibid="bib14" firstref="ref15"></nolink> <nolink nlid="nl7" bibid="bib817" firstref="ref16"></nolink> <nolink nlid="nl8" bibid="bib13" firstref="ref27"></nolink>
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  Data: The authors survey admissions coordinators about the importance of application components in admissions decisions for economics PhD programs. The survey explores the importance of difficult-to-quantify aspects such as a targeted personal statement, strength of letters of recommendation, extracurricular activities, and related work experience. The most important aspects of an application are GPAs in math and economics, letters of recommendation, and GRE quantitative score. The strength of letters of recommendation carries more weight than the prominence of the letter writer. Top-25 programs place a higher value on undergraduate program rank (for students from both domestic and international universities) and strength of letters of recommendation.
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