Is it Thanksgiving without the turkey?

I was recently talking to a friend about Thanksgiving dinner. He was complaining about the difficulty of cooking turkey and asked how my household dealt with the issue. My response? We just serve chicken instead. It’s cheaper, easier to make, and frankly turkey isn’t significantly better.

That begs the question though: can you have Thanksgiving without the turkey? What makes Thanksgiving, Thanksgiving? Being around loved ones is necessary, but not sufficient. We’re, presumably, around loved ones for most holidays. What distinguishes today from other days?

I think it’s the pumpkin pie, but what about my fellow note writers?

#microblogging

The Cost of ‘Free’ – or why I don’t like freeware

This is a partial response to Fabio Rojas recent post on the fate of Stata, a statistics package, given the rise of a free alternative, R. Rojas and others have many reasons for why R is a good package, but for now I wish to deal with the argument that it being ‘free’ is a virtue.

R is free, but I see it as a fault because it reveals that it doesn’t have a devoted support system and because it isn’t free at all. It’s actually very costly!

If you’ve spent any time with an economist you should know that there is no such thing as a free lunch. If R is free we should not simply assume it is better. To the contrary we should ask why it is free. As I have tried to argue elsewhere, it is because when you purchase software you aren’t just purchasing a few lines of code. You’re purchasing the support system that comes with it. When a company purchases Stata, or any commercial software, they do so with the expectation that they can call a dedicated hotline for troubleshooting. As software has evolved you’ve seen companies experiment with pricing to acknowledge the fact that we don’t purchase a one time software but a continuous support system.

Consider Xbox or Playstation’s online services. Their use is charged on a per time basis because it costs money to run servers and provide customer support. Even ‘freemium’ games, which nominally don’t require any money to play, survive off micro transactions which enable companies to earn steady revenues in exchange for continuing support and new content. I would not be surprised if freemium statistical software is tried in the future – access to basic regressions is free but more advanced models cost money to run. I half joke.

But let’s assume you’re good at coding and don’t need much support outside of a few days reading an R book. Should you praise R for being ‘free’? No, because you still paid the time value of your time. Every hour spent learning how to code in R is an hour you could have spent doing any number of things.

Now to be clear, you may still want to learn R if it frees up your time in the future by automating X process. This post isn’t to argue against adopting R. My point is only to say that it isn’t free in a meaningful sense. Adopting R costs in the sense that you’re giving up a devoted support system and value of time equal to how long it takes you to become proficient in it.

It’s possible that once you account for those things R is still ‘cheaper’ than commercial software like Stata or SPSS. That is an empirical question beyond the scope of this post.

Some thoughts on the ivory tower; part 1: discrimination

I entered academia in 2009 when I started my bachelor’s degree and began graduate studies in 2014 when I entered a master’s program. I have been in the ivory tower in some form for almost a decade. Others have spent much more time in the tower than I, but I am hardly a newcomer. I hope then that I can offer thoughts on discrimination and mental health in the ivory tower.

In the past few years I have noted an increased self-aware discussion on the lack of diversity, both in terms of phenotype and ideology, in the ivory tower. The tower is full of center-left white men. I have seen various formal (e.g. #womenalsoknowstuff ) and informal groups groups advocate for greater inclusion in the tower. For the record there are non-leftist groups involved in this as well. CU Boulder has a program to increase conservative intellectuals. The Institute of Humane Studies (IHS) essentially serves to advocate for classical liberals in the tower. 

There is nothing wrong with these goals. Women also knows stuff tries do this by advertising the work of female scholars. IHS does it by inviting classical liberals to book discussions – and providing beer. Both approaches sound sensible to me. My concern is that ultimately the pipeline isn’t being fixed. Not really. Both approaches help those who managed to enter, at minimum, graduate school but do little to help solve more structural reasons for why there respective groups are rare in the tower.

Why are there so few women and classical liberals (and especially so few classical liberal women!) in academia? It’s partly cultural and partly institutional.

Minorities get made fun of in academia. Academics like to think of themselves as cosmopolitan, but it’s a big lie. A recent undergrad thesis by a Berkeley student looked at misogynistic discussions on an online forum frequented by economists. I disagree with the research design of the paper, but I believe the general argument that the tower is filled with misogyny. I also believe it’s filled with dislike for conservatives, Christians, atheists, whites, blacks, Arabs, Chinese, etc.

I don’t think the tower is unique in this. Human beings divide themselves by groups and I don’t see why that will ever change. I think the academy is just a bit whiter and a bit more lefty because of sorting effects. You can see this happening even within the tower. Classical liberals sort into economics – how many classical liberal anthropologists do you know? Not counting NoL’s chief editor? Some minorities sort into ethnic studies. How many black game theorists do you know? Native American psychometricians?

What can we do? I’m not sure. We can improve the pipeline so that grad students, and eventually faculty, get more diverse. However I suspect the sorting problem will remain. Superficially we will have more diversity, but is it really diversity if we’re sorted by discipline and subfields? Should we force new classical liberals to enroll in sociology grad programs? I don’t know. Maybe we should give up on diversity all together and focus on abolishing the state. Maybe? Who knows? What do you  all think?

By the way if you want to know what true cosmopolitanism is, visit an inner city. True cosmopolitanism is seeing blacks, Mexicans and Koreans eating pupusas made by a Honduran. Everything else is a GAP commercial concoted by HR people.

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.

Race as a bundle and its implications

As I mentioned in my last post, I have been given the topic of race increased thought recently.

One of the recent developments in political science has been thinking of race not as a dichotomous variable, but as a bundle of related but distinct characteristics. Race is not simply phenotype, but a mixture of such things as one’s dialect, diet, and socioeconomic status among other things.

RaceBundle

The idea to me seems obvious, which makes me inclined to believe it. The thing is, if we take this broader approach to what race is, what are the implications for prior work not only in regards to race but the effect of demographic characteristics generally.

Race is already difficult to conduct research in because it is assigned at birth which makes it difficult to manipulate and which influences other characteristics we would ordinarily ‘control’ for in statistical analysis. To my knowledge there isn’t a ‘race ray’ that we can use to randomly assign being ‘black’ in an experiment. Tracing causality is possible, but difficult enough even in ideal situations.

Take for example the gender wage gap argument. When you control for education, presence of children, and other characteristics the gap in wages between males and females vanishes. However many of these characteristics are impacted by one’s gender. While females are not discriminated against ceteris paribus, being female does increase one’s likelihood of having to be the primary care taker for children and has historically decreased educational outcomes. In this broader sense there is a gender wage gap.

What can be done about it though? Men can try to share more of the house duties with their wives, but my general observation in life has been that children prefer being cared for by their mothers over their fathers. Should we try to do something about it? Are there advantages to one member of the household specializing in housework?

Or, if you prefer to think of the question purely in regards to race let us consider crime rates by race. I am not convinced that blacks have any higher propensity to crime than whites. However blacks are more likely to grow up in poverty and have lower educational outcomes than other races, which in turn leads to higher crime rates statistically speaking. Where should the arrow of causality be pointed towards: race, education, socioeconomic status?

Race is a difficult concept to think about. However it is precisely the difficulty with discussing it which begs that it be thought about more. I believe we liberals have a particular duty to think about race more because if we don’t then our ideological rivals will continue to dominate the conversation.

See here for an un-gated draft of the relevant paper: Sen, Maya, and Omar Wasow. “Race as a Bundle of Sticks: Designs that Estimate Effects of Seemingly Immutable Characteristics.” Annual Review of Political Science 19 (2016): 499-522.

On Liberalism & Race

Race has occupied my thoughts for the past few months. I have traditionally been against giving too much thought to race. Progressives, I think, abuse claims of racism to shut down discussions and pass questionable public policies; e.g. “We need state provided health care because the current system is racist against people of color.”. Conservatives likewise use racism (nativism really) to justify restrictive migration policies. My default position has been that liberals should seek to reduce the role of race of society. I am no longer convinced that this is a viable goal.

My earlier position was based on my childhood experience growing up in 1990s Los Angeles. I grew up in the city’s Koreatown district. The corner grocery store was owned by an Indian. We had a mosque in the block that catered to the neighborhood’s Bengali population. This being Los Angeles there was of course a mixture of Hispanics from Mexico, El Salvador, Argentina, and other nations. With so many groups clustered together in a small place you would expect frequent violence – but there wasn’t. Property crimes (petty theft mostly) were common given the general poverty in the area, but inter-group violence wasn’t common. The reason for peace was because the United States’ market oriented institutions discouraged such violence. All the groups were too busy trying to make money to have time to escalate inter-group conflict beyond making fun of one another in private. I grew up hearing plenty of jokes at the expense of Salvadoreans and Asians, but I never saw any actual violence against them. I figured that this was evidence that a liberal society would in the long run be able to make race irrelevant by making it too costly to be racist.

The events of the past few months have made me skeptical of this. Liberal society certainly makes racism costly and reduces inter-group conflict. However liberal society does not eliminate all inter-group conflict or remove the underlying differences across races.

Given that liberalism cannot eliminate racism, what should the liberal position on race be? I have no solid answer. Thoughts?

Public Support for OReGO: Preliminary Results

tldr version;

Road pricing can be a useful means of addressing infrastructure fiscal issues, reducing congestion, and improving environmental quality and it has a chance of being implemented if advocates focus on mobilizing urban voters.

Thanks to all respondents.


This post is a quick detour from the NoL Foreign Policy Survey posts.

Among other projects I am working on, I am tinkering with a public opinion project aimed at the OReGO project. The OReGO is a pilot program operated by the State of Oregon to experiment with an alternative to the existing gasoline tax. Currently Oregonians pay 30 cents per gallon of gasoline, on top of the federal 18.4 cent per gallon tax. Volunteer participants of OReGO instead pay a charge of 1.5 cents per mile driven on state roads.

orego

The primary goal of the program is to find a better way to fund the state’s infrastructure. The current system is inadequate because automobiles are becoming increasingly more fuel efficient and so, on a per mile basis, pay less for road use. Despite paying less these automobiles still rack up costs in road damage.

Advocates of OReGO, and other road pricing schemes, also hope that the program will serve as a means of combating congestion by making drivers more conscious of the marginal cost of their driving and encouraging them to avoid excess driving. The gasoline tax does this already, but very crudely in comparison.

Some advocates also hope to use road pricing as a means of improving local environmental quality and addressing climate change. Automobiles are a significant source of pollution and so reducing their use would yield environmental benefits. Even if the program kept the same number of cars on the road it could reap benefits if it reduced stop and go traffic; automobiles pollute more in stop and go traffic than free flow.

There is quite a bit of research from economists and urban planners on the issue, but public opinion research on it is relatively rare. What research exists tends to focus on either toll roads or in foreign regions. The reason for the gap in the literature is simple enough to explain – no jurisdiction in the United States has adopted road pricing. There have been a few small scale experiments, but they were largely engineering tests and surveyed only the opinion of participants. I hope to fill this gap in the literature by (eventually) conducting a large scale public opinion study of Oregonians.

The below pilot study had 220 respondents recruited through various Oregon sub-reddits (e.g. Portland, Eugene, and Salem). Respondents were obviously not representative of Oregon at large. The sample size was also small for an academic study of Oregon and there is a lot of noise. Most of the results presented are statistically insignificant. As a convenience sample though this survey was nonetheless useful. My goal in this survey was more about testing the survey before fielding it more broadly.

I thank all respondents to the survey – you’ve all helped the progress of science.

Survey Experiment Results:

The survey had a survey experiment. The purpose of survey experiments is to see how changes in phrasing, or other survey elements, influences response.

The experiment was in how OReGO was presented. Respondents were split into three sub-groups and received slightly different explanations of the program. In the base scenario they were told the program was simply a funding mechanism. In the congestion scenario they were also told about its possible congestion benefits. In the final they were additionally told about its possible environmental benefits.

OReGo is a pilot program currently being operated by the Oregon Department of Transportation. Participating drivers are being given the opportunity to pay 1.5 cents per mile they drive on public roads instead of the current 30 cent per gallon tax that the state of Oregon currently charges.

Advocates of OReGO, and similar road pricing schemes, argue that the program serves as a more dependable means of funding infrastructure than the current gasoline tax. They point out that as vehicles become more fuel efficient the amount that drivers pay per mile is decreasing, but costs associated due to road damage are not similarly decreasing. This means that in the long term the current gasoline tax will be unable to cover infrastructure costs. (/End of Base Scenario)

Advocates of OReGO also point out that the program can help reduce congestion by discouraging excessive driving and encourage the use of alternative means of transportation such as bicycling, walking, or transit. Although drivers currently pay for their automobile use in the form of the gasoline tax, many view it as a fixed payment. OReGO, which is charged on a per mile basis, may serve to make drivers more conscious of the marginal cost of their driving. (/End of Congestion Scenario)

OReGO could lead not only to reduced congestion, but could also serve to improve local air quality. One of the major sources of air pollution is automobiles, especially in stop and go traffic. (/End of Environmental Scenario)

Looking at support for adopting OReGO within five years the different treatments are little different from one another. The congestion treatment received a decline in support, but it is pushed back up in the environmental treatment.

I regret not adding a fourth group where respondents are told about the base option and the environmental benefits, but congestion is not added. As it is, it is hard to tell if the decline in support for OReGO in the congestion treatment is because people don’t care about ways to address congestion, or they dislike attempts at social engineering.

favororegobytreatment

When we look at treatment effects among only those who identified living in an urban area the effects get more interesting. Urban voters were very responsive to the idea of environmental benefits and increased support for OReGO by over 10 percentage points.

FavorOregobyTreatmentUrban.png

 

favororegobyurban

What seems to be driving the difference in support for OReGO is inter-regional differences in perceived local air quality. Those who perceive local air quality to be ‘very good’ are least likely to support OReGO. This finding is exaggerated when looking at only urban respondents.

I played around to see if this was a statistical artifact from the above treatment; i.e. it is possible those who lived in ‘very good’ air quality regions received the ‘environmental treatment’  and I am picking up the latter effect. This was not the case.

favororegobylocalair

favororegobylocalairurban

Is this a simple case of those living in high quality areas having no interest in improving the region? A “I have mines” attitude. No. When I look at support for OReGO by how respondents judged local air quality had changed in the past five years, those who thought their local air quality was improving also had the highest support for OReGO.

There is a definite relationship here between support for OReGO and perception of one’s local air quality. I can’t put my finger on it just yet.

favororegobychangeairurban

Bonus result: daily bicyclists are those most supportive of OReGO.

favororegobybikefreq

Libertarians on Climate Change

This post is part of the preliminary results of the NoL Foreign Policy Survey 2017 Pilot. I will be posting results throughout the week as I play around with the data. As always, I strongly emphasize that this is a pilot survey and these are just preliminary results

Are libertarians climate change deniers? No. The majority agree that it is occurring, caused by human activity, and that it is harmful. They do not however support unilateral action by the United States government. At least not the average libertarian respondent.

climatechange

Note that the last question, asking about supporting unilateral action, is on a different scale from the other three.

 

When you drill down by type of libertarian though you start to see stark differences. Left-libertarians agree much more strongly that climate change is occurring, caused by human activity, and harmful. They are also much more in support of unilateral action to prevent climate change.

climatechangell

 

What is driving the differences between type of libertarian? Part of the story seems to be that those who think climate change is harmful are more willing to act to address it, but I suspect a large part of the story is also that some libertarians, particularly market anarchists, simply do not trust the government. Market anarchists are less likely to believe climate change is harmful or caused by humans compared to libertarians at large, but the big difference in opinion is whether the government should act on it.

Thoughts? Tomorrow I will be posting the demographics of those who took the survey.

climatechangema

Update: Updated graphs; minor coding error.