Emily Shaw

Governor LePage’s unexpected entry into today’s emergency meeting of the Appropriations and Fiscal Affairs Committee provides yet another cliff-hanger in the dramatic series of interactions between legislators and the governor. (In other news, why yes, we will all be tuning in next week for another exciting episode of As the Statehouse Turns.)

It is highly unusual for governors to attempt to intervene directly and personally in the work of legislative committees. Why would the governor decide to step into the legislature’s process in this way?

It would be a fairly silly thing for me to attempt to divine the intentions of our governor. Given his demonstrated preference for confrontation over compromise, however, it seems unlikely that he was trying to work with the committee members.

So what else could he have been trying to do?

It’s hard not to put this action together with his active recent veto record and see it as an attempt to remind Republican legislators that he cares very much about the budget solutions they develop. Through his active veto, the governor has shown two things: first, that he’s been able to support Republican legislative preferences by killing bills that Democrats preferred (LD 272, LD 6, and LD 405), and second, that he commands enough loyalty in the legislature to sink any bill, including those passing with unanimous support (LD 49 and LD 521).

We can think of the first element of this as a carrot (allowing Republican legislators to have the final say on bills they don’t like, despite being in the minority) and the second as a stick (letting Republican legislators know that they depend on the governor’s good will in order to have their bills get past his veto.)

As a realistic Rep. Fredette observed, “There will be many tough decisions ahead on many tough issues, and we will have to work and communicate with each other and the chief executive, working to get the important work done for the people of the state of Maine.”

Caught between a rock and a hard place, they are. I really wouldn’t want to be at the other end of Robert De Niro’s “I’m watching you” hi-sign either.

Governor LePage’s vetoes so far:

1. April 2

Which bill? LD 49,  ”An Act To Amend the Laws Governing Payment of Fees to Registers of Deeds.”

How did the governor justify the veto? Protest veto, because the legislature should be worried about more pressing matters.

Original vote? Passed unanimously.

Override votes? Override passed in the House, failed in the Senate.

Representatives switching their votes:

CLARK of Easton
GIFFORD of Lincoln
LIBBY of Waterboro
LONG of Sherman
TIMBERLAKE of Turner
WILLETTE of Mapleton

Senators switching their votes:

BURNS of Washington
COLLINS of York
CUSHING of Penobscot
FLOOD of Kennebec
HAMPER of Oxford
LANGLEY of Hancock
MASON of Androscoggin
SHERMAN of Aroostook
THIBODEAU of Waldo
THOMAS of Somerset
WHITTEMORE of Somerset
YOUNGBLOOD of Penobscot

2. April 4

Which bill? LD 272, “An Act to Reduce Youth Cancer Risk”

How did the governor justify the veto? Parents want their kids to use tanning beds. “Instead of the current law that requires parents to give permission to their children tanning, this says that children are banned from it, regardless of what the parent thinks. This is government run amok. Maine parents can make the right decisions for their families.”

Original vote? 91 Y/56 N in the House (60% support), 19 Y/16 N in the Senate (54% support).

Override vote? Failed in the Senate, with same votes as the original passage – no vote-switching.

3. May 3

Which bill? LD 405, “An Act To Increase Municipal Agent Fees for Licensing and Registration of Motor Vehicles”

How did the governor justify the veto? Protest veto, because the legislature should be worried about more pressing matters.

Original vote? 89 Y/57 N in the House (59% support), 24 Y/11 N in the Senate (69% support).

Override vote? Failed in the House, with  5 Republicans switching from Yes to No and 3 Democrats switching from No to Yes.

Representatives switching their votes:

BRIGGS of Mexico
KAENRATH of South Portland
MORRISON of South Portland
KNIGHT of Livermore Falls
MacDONALD of Old Orchard Beach
NEWENDYKE of Litchfield
POULIOT of Augusta
WOOD of Sabattus

4. May 7

Which bill? LD 6, ”An Act To Prohibit a Requirement That a Superintendent Reside in the School Administrative Unit”

How did the governor justify the veto? The law would override municipal preferences and also the legislature should work on more pressing matters.

Original vote? 115 Y/22 N in the House (76% support), 28 Y/6 N in the Senate (80% support).

Override vote? Failed in the House, as described in my earlier post.

Representatives switching their votes:

AYOTTE of Caswell
BEAULIEU of Auburn
BLACK of Wilton
CHASE of Wells
CLARK of Easton
CRAY of Palmyra
DOAK of Columbia Falls
DUNPHY of Embden
DUPREY of Hampden
FITZPATRICK of Houlton
FREDETTE of Newport
JACKSON of Oxford
JOHNSON of Greenville
KINNEY of Limington
LIBBY of Waterboro
LOCKMAN of Amherst
LONG of Sherman
MacDONALD of Old Orchard Beach
MAKER of Calais
MALABY of Hancock
MAREAN of Hollis
McCLELLAN of Raymond
McELWEE of Caribou
NEWENDYKE of Litchfield
PARRY of Arundel
PEASE of Morrill
SANDERSON of Chelsea
SIROCKI of Scarborough
TIMBERLAKE of Turner
TURNER of Burlington
TYLER of Windham
WEAVER of York
WILLETTE of Mapleton
WINCHENBACH of Waldoboro
WINSOR of Norway
CHIPMAN of Portland
DICKERSON of Rockland
KAENRATH of South Portland
KORNFIELD of Bangor
RUSSELL of Portland
SHORT of Pittsfield

5. May 13

Which bill? LD 521, “An Act To Change the Budget Approval Process for Alternative Organizational Structures”

How did the governor justify the veto? School districts should not be allowed to choose meeting votes for their budgets rather than referendums. (Also, please ignore my veto rationale of last week. Tx.)

Original vote? Unanimous support.

Override vote? Failed in the Senate by one vote.

Senators switching their votes:

COLLINS of York
CUSHING of Penobscot
HAMPER of Oxford
KATZ of Kennebec
LANGLEY of Hancock
MASON of Androscoggin
PLUMMER of Cumberland
SHERMAN of Aroostook
THIBODEAU of Waldo
THOMAS of Somerset
WHITTEMORE of Somerset
YOUNGBLOOD of Penobscot

6. May 17

Which bill? LD 319, “An Act to Provide Tax Fairness to Small Businesses in the State”

How did the governor justify the veto? Doesn’t want to join a multi-state agreement, thinks the federal government should take care of issues related to taxing internet sales, and doesn’t want the legislature telling Maine Revenue Services what to do.

Original vote? Unanimous support.

Override vote? Predict it will pass the House, fail in the Senate.  If the override fails in the House, this will represent the largest number of legislators switching their votes yet and demonstrate the biggest impact of the governor’s veto on Republican legislative behavior to date.  In the Senate, I expect to see a similar group switching votes as those that did so on LD 521. I’m particularly interested in what Senator Katz will do – first, because he’s my own Senator, and also because I think he’s a valuable indicator of the preferences of the moderate Republican caucus.

The Portland Press Herald is exploring the shift in vote among Republican state representatives on LD 6, the bill that would allow municipalities to decide whether or not they want to require their superintendent to live within the school district. This bill passed with a strong supermajority of votes in April - over 75% support in both chambers – but was just vetoed by Governor “School Choice” LePage.

In theory, this shouldn’t have been a problem for the bill because a gubernatorial veto can be overridden by a 2/3 majority of legislators. This bill had far more support than that. However, here’s where politics steps in on our theories about consistency. 41 representatives changed their vote between April and May. 35 of those 41 were Republicans, who moved from supporting to opposing the bill. Since Governor LePage is the highest-profile Republican in the state, it is hard for Republican legislators to cross him without having reasonable cause to believe that negative consequences will follow.

This bill wasn’t even a strongly partisan bill. Support and opposition initially seemed to have more to do with local preferences than party – southern Mainers of both parties tended to support it, while representatives from other regions varied more. Initially there were 8 Democrats and 12 Republicans opposed to it. Two of the four Independent (“Unenrolled”) representatives supported it and other two opposed it. Nonetheless, even on something as relatively non-partisan as the decision whether to allow municipalities to determine the conditions of their superintendents’ employment, the governor’s veto drives some Republican legislative vote-changing.

Interestingly, as it turns out, the governor’s veto also drove some Democratic – and even Independent – legislative vote-changing! 5 of the 41 vote changes were among Democratic legislators, and 1 of the 2 Independent legislators changed his vote. All of those changes were moves in support of the bill. I hadn’t really thought about that kind of effect before looking, but I can imagine two causes for it. One is the governor’s unpopularity among Democratic voters. It’s possible that a legislator’s history of voting to override gubernatorial vetoes will be attractive to Democratic voters during the next election regardless of what the bill in question was actually about.  Another possibility relates to vote-whipping or lobbying by particularly effective bill sponsors. If that was the case, we should see different patterns of Democratic vote-switching depending on the issue or legislators involved.

At any rate, as we get into a period of increasing chamber votes and the Governor warms up his vetoin’ hand, it will be useful to have some ways to visually represent the impact of gubernatorial veto on legislative decision-making. I am excited that the Press Herald is thinking about ways to represent this visually, but I think they haven’t quite got it right yet – right now they’ve spread the visualization across two different pages, which makes it difficult to compare them. I can completely empathize; it’s really challenging to figure out how to convey information in a succinct, compelling visual which also contains a lot of information.

Just trying to think with them, though, about how to convey vote-changing visually. We’re going to be doing more of this, so we might as well explore our options! The relevant data source here is the set of roll call votes for this bill. Since there was only a veto-override vote in the House chamber, we really only need to look at the House roll-calls for LD 6 in April and May. A vetoed bill must must obtain 66% support in both legislative chambers to override the governor’s veto. (Incidentally, to see how your own legislator votes on any bill of interest to you, you can find roll-calls linked on the left-hand side of the bill summary pages.)

Here’s a summary of the vote totals:

April: 115 yes (74D, 39R, 2U), 22 no (8D, 12R, 2U) = 84% support among those voting, 76% of total chamber (including absent)

May: 86 yes (81D, 4R, 3U), 56 no (2D, 53R, 1U) = 60% support among those voting, 57% of total chamber (including absent)

The votes don’t add up to the same number because different numbers of representatives were absent on each voting day.

Clearly, the interesting story here is the vote-changing. Here’s one simple way to visually explore vote-changing by party. It’s easy to understand, but there’s not a lot of detailed information in it.

I converted the number of yes and no votes to percentages of total party members in order to compare trends by party. There are more Democrats than Republicans in the House, so if you don’t do this it makes it harder to compare party trends.

However, this visual misses some of the relevant information. Especially if you’re the Press Herald, you want to be sure to get legislator’s names in there somehow, so people can know how their own legislators voted and whether they changed, or didn’t change, their vote.

Here, and at the top of the page, my attempt at conveying that information. Click on the chart to be able to read the names.

Maybe a little closer? Not sure.

What ideas do you have for communicating visually about vote-switching?

I’ve had the Yeah Yeah Yeah’s take on the theme running periodically through my mind for a few days now, but looking at this map posted on the Bangor Daily News yesterday – describing county-level changes in female mortality – made me want to see even more maps:

Since political and socio-economic variables are often describing social conditions as much as they are describing atomized, individual preferences, maps are an excellent, intuitive way to convey information about them. I have spent a lot of time looking at election maps and income maps. Let me link a couple in here so that you can see why they occurred to me.

I tried to make a map for median county income in the blue-red spectrum for these data using American Fact Finder, but kept getting timed out. You can still see the regional connections, fairly well, however.

The third map concerns Obama’s county-level performance in 2012.

There are both broad-stroke and more finely-grained points to observe across these three maps. The consistency of the coasts is what jumped out at me first, as a Northeasterner. However, I also find the relative diversity in wealth and health outcomes across the Midwest just fascinating.  I also had never paid such attention to the relatively urban band across the Southeast, which seems to track more strongly with health than with income. (I’m looking for the data right now to do a proper analysis, but I haven’t been able to get it yet. Will update when I do!)

What do you see in these maps?

I continue to be fascinated by the  disconnect between the degree of detail available in ME DoE Data Warehouse information – and what is available in the “School Grades” data collection effort itself – and the really thoughtless application of that data to uni-dimensional and somewhat random A-F grades.  The essence of what the grading system appeared intended to communicate was evident from yesterday’s newspaper headlines:

Failure and shame were the watchwords of the day. It was somewhat serendipitous that Slate.com published an article yesterday entitled, “The Case Against Grades: They Lower Self-Esteem, Discourage Creativity, and Reinforce the Class Divide.” Many of the same dynamics appeared poised to occur as a result of the ME DoE decision to try to “improve” Maine schools through unfairly labeling them with golden As through scarlet Fs.

And what do we mean by unfair? A large part of it certainly has to do with the fact that the “school grades” relate so strongly to income. If most of the variation in school scoring can be explained by local wealth, then all these grades do is affirm poor towns as failures and wealthy towns as wonderful and desirable. (As if everything else in American culture isn’t already reinforcing this belief.)

However, there were smaller and stranger injustices lodged within the system that I discovered when I look at the raw scores before the assignment of letter grades.

How were the raw scores created? For both the high school and sub-high school grading methodologies, the DoE took into account math proficiency, growth in math proficiency, reading proficiency and growth in reading proficiency. For high schools, the DoE also looked at four and five year graduation rates and ranked them on a 0-50 scale. For elementary and middle/junior high schools, the DoE looked at growth in reading and math proficiency for the lowest 25% of student test-takers.

I noted in my addition to yesterday’s post that the state academies — which really are examples of innovation in relatively impoverished areas, the kind of thing that Commissioner Bowen and Governor LePage give lip-service to appreciating — were heavily penalized for lower standardized test participation, something that state law had permitted them to do.  This is likely to matter a lot to the state academies, too, because they subsidize their education by attracting full-tuition students. The decision to arbitrarily punish them for something they had been allowed to do is likely to cost them real dollars in terms of reduced full-tuition enrollment.

The penalty for not having more students take a test which they were not required to take was to drop them a grade lower than their score would have otherwise predicted. For example, look at this section of my Excel sheet:

Ranking of raw scores and grades don’t necessarily correspond. Why? Because the ME DoE decided that student participation rate had to “count” somehow. This was the bluntest and least logical way to achieve that end.

Another strange injustice, however, was the decision to create arbitrary new cut points to determine which schools would get each of the “school grades.” Looking at the distribution of the raw scores, there was no obvious way to produce the particular set of grades that the DoE decided to assign. Here, for example, is the distribution of scores in terms of what proportion of the maximum possible score assigned by the DoE was achieved by each school.

Under a traditional grading scheme, this would mean that most of the schools fail and the second largest group get Ds. Now, let it be said that there’s nothing particularly necessary about the grading methodology that the DoE developed. This was their baby – they could have developed any weighting, any grading scheme. Yet even within their own grading scheme the cut points are arbitrary and don’t communicate anything real accurate, in terms of proportions, regarding what was produced by their own dataset. They didn’t say “most of Maine schools fail.” Instead, they said something different:

In blue, you see how schools would have been graded if you just took the scores that DoE found that they achieved, through the DoE’s own grading system, at face value. In red, you see what the ME DoE decided to assign. The proportions are nowhere even similar to what their test scores found. Instead of reporting a clear assessment of how schools were doing according to some presumably meaningful set of criteria, the DoE decided that it wanted to see a certain structure to its outcomes — mostly Cs, with a meaningful number of B and Ds, with fewer As and Fs. Since this profile is not naturally available in the data they collected, they just…made it happen.

All those headlines about “75% of the state at C or less” were absolutely meaningless, because the only reason that they are like that is because the DoE decided to report them as such.

Okay. With that very relevant issue out of the way, I wanted to spend a little more time looking at the fit between the poverty/school score relationship and its residuals. I looked at high schools, junior high/middle schools, and elementary schools and found that there were three very different kinds of relationship between poverty and school scores depending on the school level.

For high schools, poverty levels were very, very determinative of outcome. I said in my post yesterday that poverty levels explained around a third of school grades. Looking at more finely-grained outcomes – the raw school scores – and more finely-grained inputs – just high schools – I found that poverty accounts for nearly two-thirds of raw school scores.

That is really, really high. Most of a score for each individual high school, across its level of variation, can be predicted by how many kids get free lunch. The biggest outlier in this trend – that one little dot at the top – is the Maine School of Math and Science, which is so sui generis it probably shouldn’t even be included in this kind of measurement.

Giving high schools grades without accounting for poverty levels is really just telling kids that they are failures for being poor and teachers and administrators that they are failures for choosing to work in impoverished areas.

Wouldn’t it be more interesting to find out how much individual school add (or reduce) value relative to what was predicted by average school poverty level? On that subject, here are the residuals that I calculated for this relationship. I threw in the ME DoE scores next to the residuals just for funsies. What different characteristics of “good schools” do these two different kinds of measurement measure?

As I described in yesterday’s post, looking at the residuals allows us to control for large, important variables like poverty levels in order to start looking at other contributing factors – for instance, like teaching methods, relationships with the community, curricular innovations, you know. Things that we’re trying to do in order to PRODUCE better schools. Looking at the residuals, Waterville Senior High is scoring 10% higher relative to the maximum possible score than its poverty levels would predict – similar to Cape Elizabeth High, in fact. Why is that? Wouldn’t you like to know?

Returning to the question of the strength of the poverty/score relationship, this does  start changing when you look at different school levels. Here is the scatterplot for  elementary schools:

Note how much more distant many dots are from the trendline in the middle, compared with the tighter cluster in the high school chart. That is what a weaker relationship looks like. Here, the R^2 tells us that only around a quarter of the school score results is explained by the school’s percentage of students receiving free or reduced lunch. That is VERY interesting, and worthy of further attention.

Here are the residuals for elementary schools.

It is also interesting that the strength of the relationship between middle/junior school scores and poverty fall between the two school groups, but much closer to the high-school strength of relationship.

What is it that happens between elementary school and middle school that leads to such different outcomes? Is it difference in the standardized tests? Something truly different about how middle school and elementary school students are taught? Something else?

Another fascinating, fascinating set of questions which are not approached – not even raised – by the arbitrary, unfair flat “school grades” that our state DoE decided to issue. What a missed opportunity.

Today’s much-anticipated release of the Maine Department of Education’s “School Grades” has provoked the similarly-anticipated, and likely intended, negative response from educators who called the grading system “flawed” in public and who-knows-what in private. The Maine Education Association has certainly won this round on Twitter and in the newspaper online comments section, with an overwhelming number of responses criticizing the grading methodology. Stephen Bowen himself seems to be resigned to expressing an awkward optimism about the whole thing:

I commend him on resisting the urge to use an exclamation point on that second sentence. I’m intrigued by his application of the Sheryl Sandberg “lean in” concept to parenting. In general, I don’t hold Stephen Bowen entirely blameless for this mysterious attempt to randomly shame a bunch of schools, but one sees the hand of the Big Man quite clearly in this whole enterprise.

Again, the Maine Education Association has been quite successful so far in steering the conversation to the fact that the DoE school grading system bears a strong, linear relationship to average district poverty as measured by percentage of students qualifying for free or reduced lunch. One presumes that Bowen and Governor LePage were not prepared to pre-emptively address this extremely valid concern because the whole school grading idea is essentially another route to shoehorning more charter schools (and preferably virtual, Floridian charter schools) into the state, as this appears to be pretty much the Governor’s entire raison d’etre with regard to intervention in Maine’s public school system. Otherwise, one can only assume that the always-significant relationship between income and school performance would have been something they chose to address.

I have not yet studied the entire methodology behind the school grading system, although others are raising issues about such problems as cut-off points for the letter grades, the significance of the number of students tested, and the imposition of a bell curve on the grading results. However, for the sake of argument let’s assume that the grades are a straightforward assessment of average standardized test scores and improvements over previous years on those test scores. (Yes, I know – large grain of salt.) What would those results tell us?

As the MEA and Mike Tipping point out, there is a very strong relationship between levels of poverty and average district ME DoE “school grades.” The averages in these areas are quite telling, with each an average increase of around 10% of district students receiving  free or reduced school lunch for every step down in average district “school grade.” However, the averages are not identical to each district’s score. I used the DoE’s much improved new data interface to download the percentages of students receiving reduced or free lunch and looked more closely at how these variables related to one another.

As you can see, although the general trend is quite clear, there are a number of schools which do not fit exactly along the line. The black line in the center of the scatterplot describes the predicted relationship between poverty and “school grade.” While those relationships tend to cluster next to the line they are not all right on it. The distance between the dot – the actual relationship – and the line – the predicted relationship – is known as the observation’s residual.

People enjoy looking at residuals because you can generally get lots of interesting information from thinking about what could explain why an observation deviates from its predicted score. In this case, we have a strong bivariate relationship between the ME DoE’s definition of quality and district wealth. The R^2 of the bivariate relationship is .32, which means that about a third of the ME DoE school grade is explained by levels of district students receiving free or reduced school lunch. However, that means that there are some other factors explaining the ME DoE school grades as well, unless it’s all just random “noise,” or inexplicable random variation.

Unfortunately, because poverty is such an important factors in predicting outcome you aren’t going to get anywhere with finding these additional explanations for school quality (per the DoE’s measurement of it, at least) unless you control for district wealth. Here’s where the residuals come in. By looking at the residuals – the distance from the line to the observed score for each district – you can see where districts are overperforming or underperforming relative to where we would expect to see them based on their average poverty levels.

This is an interesting list. If we look at “school grade”/poverty residuals – that is, “school grade” performance controlling for poverty, we find that the following school districts are overperforming relative to how their average level of poverty predicts they should perform:

To read that table, what it means is that the average Edgecomb or Whiting school is performing 2 grades above where it is predicted to perform, based on those districts’ average poverty level. The lower the residual, the closer that district is to having its performance on the “school grades” be predicted almost entirely by district income.

Now, lots of districts also fell below where their income predicted they should score. That’s just the hard truth of OLS regression, folks.

It personally gives me little joy to show you those districts, particularly as my son’s school is among them (although not one of the more extreme cases). It is interesting to note, however, that the bivariate relationship is in fact not perfectly linear, as demonstrated by looking at the moving averages. Districts with fewer than 15% of students receiving free or reduced lunch, on average, outperform their expectations based on the average relationship between poverty and “school grade.” After that number, the average performance more accurately predicted by poverty level.

(Sadly, Excel does not allow me to show a smoothed version of this measure. But you get the idea.)

Another interesting thing about the group of schools getting “school grades” below their predicted score is the number of state academies in the group. (For those not in the know, state academies were Maine’s original “charter school” – we were doing charter schools before charter schools were hip. They are public-private schools which create their own employment rules and receive town money, in addition to attracting full-freight-paying non-local students.) Only Erskine Academy added “school grade” value beyond what was predicted through income level, while six academies did not. It very well could be that there’s something important and systematic about the students who are sent to state academies, but it also could be telling for what we should expect to see out of the charter schools the next time  these “school grades” are given.

**ETA: Thanks to Jonathan Pratt for bringing to my attention the fact that the academies had not in previous years been required by the state to participate in standardized testing in the same way. Because they had an exception around testing, they had lower participation – yet under  the ME Doe “school grades” scheme they were summarily dropped one letter grade below what their raw score would have given them otherwise. Why  the ME DoE decided to treat the academies in this way, yet altogether exclude other schools – like charters, or very small schools – from their grading system is really a total mystery. I will recalculate the regression based on the raw scores later today.**

Unless this “school grade” business was actually a one-off experiment intended to provide justification for adding more charter schools. Which would be simply shocking. Consider me shocked — shocked! — in advance.

If it isn’t entirely a farce, however, I would expect to see Commissioner Bowen speaking reasonably about the significance of poverty and the “school grade” system — pointing out both what poverty explains, as well as trying to see what it doesn’t.

It’s the end of an absolutely gorgeous early spring day in my medium-sized Central Maine municipality (pop. 6,183.) Warming mud, running water, lots of sun and, in my case, a freshly washed and clipped dog. We all took a walk in the woods and admired the new streams, let maple sap fall into our open mouths, did some outdoor chores while the kid enjoyed squishing his bare toes in the mud, and observed the snow existing in the loose, large-crystaled, SnoCone-like state it has just before it disappears. It simply doesn’t get any better.

In my opinion, a day like today shows off the perfect state of municipal services in a town my size. Our roads, though not numerous, are good. Crime is low, as it is in Maine generally, and I happen to know one of our few police officers because we both have a child in the same cute elementary school. We wouldn’t have had a whole lot to do if we had chosen to go downtown instead of into the woods for our walk because there isn’t much of a “there” there, to quote Gertrude Stein speaking about a different Oakland. (I used to live in that different Oakland less than 10 years ago, and not very far from the sign in the linked picture. There might not have been much “there” there, but there was a whole lot more “there” than there is in this Oakland, if we’re talking about “there” in the more conventional, city-minded sense.) Our private well provided our water, our own septic tank takes care of sewage, and the fact that we have to bring our own trash and recycling to the dump (sorry! Transfer station!) gives us a slightly smelly but not-totally-unpleasant set of Saturday-afternoon outdoor chores to do together.

However! Would this be a reasonable day in a larger town? Unlikely. Not only does a town with a higher population reduce the likelihood that everyone will be able to walk in the woods behind their house, or have a well and septic system to serve their water and sewer needs, but people who live in a larger town might also do so because of a difference in preferences. They might actually want to spend the afternoon downtown. Once there, they might want to walk around a park, or bring their children to a playground. They would expect their town to be well-lit for the activities they pursued after 6pm. Restaurants and retail establishments seeking to attract customers might have higher expectations for cleanliness and street repair than I do.

Let’s look at how this plays out in terms of per capita expenditures at different municipal sizes. The first variety of expenditure examined in the Fiscal Survey is General Administration. This category includes employee salaries and benefits, board expenses, legal expenses, offices, government buildings, and economic development. Do we see the concept of economies of scale in terms of per capita costs for local government administration demonstrated here?

Not really. In fact, the per-resident cost of government administration decreases in linear fashion as towns get smaller – again, with the exception of the tiniest towns, where perhaps economies of scale are finally kicking in.

Why might this be, that people in larger towns are paying more – not less -per person for local government administration? One reason for this difference may be that they expect different services from their municipal governments. For example, economic development. Almost all of the municipalities with more than 10,000 residents had some sort of economic development department (i.e., listed economic development expenditures in their budgets) while almost none of the tiny municipalities did. The town sizes in between demonstrated a nearly perfect linear relationship in terms of their likelihood of funding economic development activities.

Town size relates to having – or not having – other kinds of services as well. As some of my interlocutors have noted, your smaller towns are not going to have large police departments. Police departments are expensive and where municipalities have them, they make up the largest part of the town’s public safety expenditures. (Other parts of the public safety budget include fire, EMS, street lighting, and related capital improvements.) However, many smaller have no police departments at all, instead contracting with county sheriff’s offices to provide local law enforcement.

Here’s median per capita public safety expenses by municipal size:

Again, the stair-step negative linear relationship, until we get to the tiny towns. Just as in general administration, there appears to be a “floor” for public safety costs, and the tiny towns have run up against it.  If there is, on average, some absolute bedrock expense below which you cannot reasonably go, then the smaller number of tiny-town residents are each simply going to have to pitch in a larger share in order to cover this cost.

So what about the expenditures for the county law enforcement that covers municipalities which  lack a municipal police department? Looking at those numbers, we find that the smaller  town categories do indeed have  higher county expenses than the larger town size categories. However, the range in median expenses in the “county expenditures” category was a lot smaller – chiefly because the overall expenses in this category were a lot smaller. Thus, even when you add county expenses to municipal public safety expenses, the larger the town,  it’s still paying more per capita for public safety.

By this point, you may be thinking, “okay, this seems somewhat ridiculous. Are you telling me that there are no economies of scale to be realized in local government? Really?”

There does appear to be one place.

Your savings are in public works.

Ironically, even though the public works category includes water and sewage (as well as dump and recycling and capital expenditures), those costs are not strongly associated with town size even though larger towns are much more likely than smaller towns to provide municipal water and sewage services. Based on the lack of size effect, water and sewage seems like a really cost efficient thing for municipalities to offer. (Except on North Haven, where water and sewage is very expensive. Why should it be 50% more expensive than it is on Vinalhaven? Inquiring minds.) However, roads are simply more expensive per capita the smaller the town. More people are driving the same roads in larger towns, leading to an economy of scale on road repair, road salting and bridge maintenance.

The economies of scale in road work seem entirely clear when we look at the negative relationship between town size and median per capita road and related expenses in town budgets.

So does this disprove my central thesis that smaller is actually less expensive?

Let’s find out!

Tomorrow….