When to list working papers?

I have been updating my CV the past weekend and as a process have spent more time than I should have looking at other’s CV for reference. The experience has reminded me of two things, (1) I do not share other’s infatuation with latex and (2) I despise how working papers are listed.

My primary concern with many CVs is that some people list working papers along with peer reviewed published papers. I cannot help but feel this is weaseling. This is not aided when people list “revise and resubmits” along with actual publications. An R&R is not a publication. By all means it is a good sign that a paper will get published, but it is not a publication.

My second concern is that people list working papers, but offer no link to a draft copy. In the absence of a readily accessible draft, how am I to know if someone has a ‘real’ working paper or simply some regression results on a power point? I am especially irked when I contact an author asking for a draft of their working paper and am told that no such draft exists.

I’m still a graduate student, but if I am to be humored I think academia would benefit if it became the norm to list working papers (and R&Rs) in a separate section and if it were required to upload a draft on SSRN (or whatever your preferred depository is).

Likewise I think it best to list book reviews and other non-peer reviewed materials separately. I was surprised the other day to find people who listed op-eds in local newspapers or blog posts under publications. Don’t get me wrong – I think some blog posts (especially those on a certain site) are great reads! But peer reviewed publications they are not.

Does this sound reasonable?

The importance of understanding causal pathways: the case of affirmative action.

Let us put aside the question of whether affirmative action is a desirable goal. Instead I wish to ponder how to implement affirmative action, given that it will be implemented in some form regardless.

The logic of most affirmative action programs is that X vulnerable community’s outcomes (Y) are significantly below the average. For the sake of example let us say that X is Cherokees and Y is the number of professional baseball players from that ethno-racial group.

Y = f(X) 

A public policy analyst who simply noted the under representation of Cherokees in the MLB, without digging deeper into the causal pathway, may propose that quotas be implemented requiring teams to have a certain share of Cherokee players. Such a proposal would be a bad one. It would be bad because it could lead to privileged Cherokees gaining spots in the MLB at the expense of less privileged individuals from other ethno-racial groups.

A better public policy analysis would note that Cherokees are less likely to enter professional baseball because they are malnourished (Z). This analyst, recognizing the causal pathway, may instead propose a program be implemented to deal with malnourished individuals regardless of their ethno-racial identity.

Y = f(X); X = f(Z) 

Most affirmative action programs that I have come across are of the former type. They recognize that X ethno-racial group is performing poorly in Y outcome, and propose action without acknowledging Z. We need more programs that are designed with Z in mind.

I do not say any of this because I am an upper class white male who resents others receiving affirmative action. To the contrary. I have benefited from this type of affirmative action several times in my life. On paper I am a gold mine for a human resources worker looking to fulfill diversity quotas: I am a undocumented Hispanic of Black-Jewish descent who was raised in a low income household. I am not however vulnerable. I come from a low income household, but my Z is not low. Not really.

Despite my demographic group, I am not malnourished. I could stand to lose weight, but I am not unhealthy. I attended a state university, but my undergraduate education is comparable to that of someone who attended a public ivy. My intelligence is on the right side of the bell curve. Absent affirmative action I am confident I would achieve entry into the middle class.

Nor am I a rarity among beneficiaries. My observation is that many beneficiaries of affirmative action programs are not low on Z and left alone would achieve success on their own. Affirmative action programs are often constructed in such a way that someone low on Z could not navigate their application process. It may seem egalitarian to require applicants to submit course transcripts, to write essays, or present letters of recommendations. However these seemingly simple tasks require a level of Z that the truly under privileged do not have.

Good public policy analysis requires us to understand causal pathway of why X groups do not achieve success at similar rates as other groups. We must design programs that target undernourishment instead of simply targeting Cherokees. If we fail to do so we may have more Cherokees playing for the Dodgers, but will have failed to solve the deeper program.

Note that I say vulnerable as opposed to ‘minority’ in the above passage. This is to acknowledge that many so-called minority groups are nothing of the sort. Hispanics, Blacks, and Asians form majorities in various parts of southwest, south, and the pacific (e.g. Hawaii). Women likewise are not a minority, but are often covered by affirmative action programs. Jews are in many instances minorities, but in contemporary life are far from under represented in society’s top professions. This distinction may seem too obvious to be worth making, but it is not. Both sides of the political spectrum forget that the ultimate goal of affirmative action is to aid vulnerable individuals.  Double emphasize on individuals.

What is the optimal investment in quantitative skills?

As I plan out my summer plans I am debating how to allocate my time in skill investment. The general advice I have gotten is to increase my quantitative skills and pick up as much about coding as possible. However I am skeptical that I really should invest too much in quantitative skills. There are diminishing returns for starters.

More importantly though artificial intelligence/computing is increasing every day. When my older professors were trained they had to use IBM punch cards to run simple regressions. Today my phone has several times more the computing power, not to mention my PC. I would not be surprised if performing quantitative analysis is taken over entirely by AI within a decade or two. Even if it isn’t, it will surely be easier and require minimal knowledge of what is happening. In which case I should invest more heavily in skills that cannot be done by AI.

I am thinking, for example, of research design or substantive knowledge of research areas. AI can beat humans in chess, but I can’t think of any who have written a half decent history text.

Mind you I cannot abandon learning a base level of quantitative knowledge. AI may take over in the nex decade, but I will be on the job market and seeking tenure before then (hopefully!). 

Know your data, show your data: A rant

I am finishing up my first year of doctoral level political science studies. During that time I have read a lot of articles – approximately 550. 11 courses. 5 articles a week on average. 10 weeks. 11×5×10=550. Two things have bothered me immensely when reading these pieces: (1) it’s unclear authors know their data well, regardless of it being original or secondary data and (2) the reader is rarely showed much about the data.

I take the stance that when you use a dataset you should know it well in and out. I do not just mean that you should just have an idea if its normally distributed or has outliers. I expect you to know who collected it. I expect you to know its limitations.

For example I have read public opinion data that sampled minority populations. Given that said populations are minorities they had to oversample in areas where said groups are over represented. The problem with this is that those who live near co-ethnics are different from those who live elsewhere. This restricts the external validity of results derived from the data, but I rarely see an acknowledgement of this.

Sometimes data is flawed but it’s the best we have. That’s fine. I’m not against using flawed data. I’m willing to buy most arguments if the underlying theory is well grounded. To be honest I view statistical work to be fluff most times. If I don’t really care about the statistics, why do I care if the authors know their data well? I do because it serves as a way for authors to signal that they thought about their work. It’s similar to why artists sometimes place a “bowl of only green m&ms” requirement on their performance contracts. Artists don’t know if their contracts were read, but if their candy bowl is filled with red twizzlers they know something is wrong. I can’t monitor whether the authors took care in their manuscripts, but NOT seeing the bowl of green only m&ms gives me a heads up that something is off.

Of those 500+ articles I have read only a handful had a devoted descriptive statistics section. The logic seems to be that editors are encouraging that stuff be placed in appendices to make articles more readable. I don’t buy that argument for descriptive statistics. Moving robustness checks or replications to the appendices is fine, but descriptive stats give me a chance to actually look at the data and feel less concerned that the results are driven by outliers. In my 2nd best world all dependent variables and major independent variables would be graphed. If the data was collected in differing geographies I would want the data mapped. In my 1st best world replication files with the full dataset and dofiles would be mandatory for all papers.

I don’t think I am asking too much here. Hell, I am not even fond of empirical work. My favorite academic is Peter Leeson (GMU Econ & Law) and he rarely (ever?) does empirical work. As long as empirical work is being done in the social sciences though I expect a certain standard. Otherwise all we’re doing is engaging in math masturbation.

Tldr; I don’t trust most empirical work out there. I’ll rant about excessive literature reviews next time.

Can we stop using Spanish for migrant services?

Before I go any further let me be clear that I am not arguing against the use of Spanish generally. Nor am I arguing against providing Spanish translations in public spaces. My concern is about the conflation of Hispanics and migrants.

I had the pleasure of being educated in bilingual classrooms during my early childhood. My entire life I have alternated between English and Spanish. When I have kids (I can dream!) I plan to educate them in both languages plus either Chinese or Japanese. I absolutely love Spanish. However I often worry that it has become too prevalent among migrant circles.

When I visit migrant groups I notice many of them have Spanish names or sprinkle Spanish slogans among their material. The worst instances of this is when ‘la raza’, the race, is used as reference to the pan Hispanic community. I can understand why they do so, Hispanic migrants probably find such gestures to be in good will and are more willing to seek help when they need it. What however of non-Hispanic migrants?

We, Hispanic migrants, often make fun of white Americans for thinking that all Hispanics (plus Brazilians!) must be Mexicans.”Guatemala? Where is that in Mexico?” Yet we fall into the same trap of thinking that all migrants are Hispanics. How must Asian or African migrants feel when they search for help but are surrounded by Spanish? It is hard enough to learn one new language, let alone two.

As I’ve mentioned before, I grew up in Los Angeles’ Koreatown. As the name suggests the area has a sizeable Korean population. I interacted with them all the time, except when it came to migrant related events. Their absence was particularly notable in services for undocumented/illegal aliens. Koreans, unknown to most, make up a significant share of undocumented migrants. You’ll rarely see them at events though. Part of it is a taboo about discussing the issue in the Asian migrant community. I can’t help but feel that it is also that we, Hispanic migrants, have made them feel unwelcome in our groups.

If migrant groups care about inclusion they should avoid the use of Spanish where possible. By the same account, can we please stop linking Cinco de Mayo and other Hispanic-linked things with all migrants. By all means have Spanish translations of your material, but also have translations in Korean, Chinese, etc etc.

Should we tax churches? A Georgist Proposal

Recently President Trump enacted a series of executive orders with the aim of extending religious liberty. This has gotten me to think about churches and tax policy. Just to be clear, in this post I will not discuss the details of Trump’s orders. I care about the broad concept here.

Churches in the United States are exempt from certain taxes due to their classification as charities. I have often been in favor of this designation. Taxes can easily serve as a way for the state to discriminate against groups subtly. I could easily imagine a tax that targets churches with kneeling pews (e.g. Catholic churches) and therefore disadvantages them relative to denominations that have less kneeling involved. I could also imagine a system, similar to some European countries, where the state collects the tithe on behalf of the church. This arrangement would favor larger, state recognized, churches at the expense of smaller start up denominations. In both cases taxes can be used by the state to effectively discriminate between churches.

Some time ago though it was pointed out to me that NOT taxing churches could also lead to discrimination against them. Take the case of property taxes. When urban planners draw up zones (residential, commercial, mixed use etc.) they effectively have the power to exclude churches from certain neighbors. Even without official census data it is not difficult to notice where certain religions sort within the city,  and so a zealous planner could easily discriminate by denomination. When church property IS taxed there is a strong disincentive against this type of discrimination because it reduces potential city revenues. Even if a given planner may be willing to discriminate nonetheless, he would find himself fired by his tax-obsessed superiors. When church property ISN’T taxed this incentive is reversed. Since church property can’t be taxed cities lose out on potential tax revenue when they zone an area for a church over taxable property. A devout religious urban planner may easily be pressured to minimize the number of churches to maximize tax revenues. I suspect a Catholic urban planner would prefer to reduce the number of Protestant churches, so this is a scenario where minority denominations could easily find themselves zoned out of existence.

The current concern about whether churches should be allowed to be engaged in politics would be moot if they were taxed. The legal reason churches are limited in their political speech is that they are classified as charities. Certain crowds would be angry about allowing churches being involved in politics* anyway, but I suspect many politicians would be fine to look the other way in exchange for the increased tax revenues.

How can we balance the pros of taxing churched (helping them avoid being discriminated by zoning and gaining political speech) versus the cons (discrimination by taxation)? I think the answer is a georgist tax on land. It achieves the goal of taxing churches without discriminating against any given denomination.

Thoughts?
_______

*For the record I personally oppose my church, the Catholic Church, from getting involved in politics. I am fine with the priest lecturing against the evils of abortion, but I don’t want to hear his thoughts on the optimal income tax rate.

Where is the optimal marriage market?

I have spent the past few weeks playing around with where the optimal marriage market is and thought NoL might want to offer their two cents.

At first my instinct was that a large city like New York or Tokyo would be best. If you have a larger market, your chances of finding a best mate should also increase. This is assuming that transaction costs are minimal though. I have no doubt that larger cities present the possibility of a better match being present in the dating pool.

However it also means that the cost of sorting through the bad ones is harder. There is also the possibility that you have already met your best match, but turned them down in the false belief that someone better was out there. It’s hard to buy a car that we will use for a few years due to the lemon problem. Finding a spouse to spend decades with is infinitely harder.

In comparison a small town information about potential matches is relatively easy to find. If you’re from a small town and have known most people since their school days, you have better information about the type of person they are. What makes someone a fun date is not always the same thing that makes them a golf spouse. You may be constrained in who you have in your market, but you can avoid lemons more easily.

Is the optimal market then a mid sized city like Denver or Kansas City? Large enough to give you a large pool of potential matches, but small enough that you can sort through with minimal costs?

P.S. A friend has pointed out that cities/towns with large student populations or military bases are double edged swords for those looking to marry. On the one hand they supply large numbers of dating age youths. On the other hand, you would not want to marry a 19 year old who is still figuring out what they want to major in.