Visualizing asylum statistics

Note: of potential interest to R users for the dynamic Google chart generated via googleVis in R and discussed towards the end of the post. Here you can go directly to the graph.

02alessandro-penso
An emergency refugee center, opened in September 2013 in an abandoned school in Sofia, Bulgaria. Photo by Alessandro Penso, Italy, OnOff Picture. First prize at World Press Photo 2013 in the category General News (Single).

The tragic lives of asylum-seekers make for moving stories and powerful photos. When individual tragedies are aggregated into abstract statistics, the message gets harder to sell. Yet, statistics are arguably more relevant for policy and provide for a deeper understanding, if not as much empathy, than individual stories. In this post, I will offer a few graphs that present some of the major trends and patterns in the numbers of asylum applications and asylum recognition rates in Europe over the last twelve years. I focus on two issues: which European countries take the brunt of the asylum flows, and the link between the application share that each country gets and its asylum recognition rate.

Asylum applications and recognition rates
Before delving into the details, let’s look at the big picture first. Each year between 2001 and 2012, 370,000 people on average have applied for asylum protection in one of the member states of the European Union (plus Norway and Switzerland). As can be seen from Figure 1, the number fluctuates between 250,000 and 500,000 per year, and there is no clear trend. Altogether, during this 12-year period, approximately 4.5 million people have applied for asylum, which makes slightly less than one percent of the total EU population. Of course, this figure only tracks people who have actually made it to the asylum centers and filed an application – all potential refugees who have perished on the way, or have arrived but been denied the right of formal application, or have remained clandestine are not counted.

asylum_applications_small

Figure 1 also shows the annual number of persons actually recognized as ‘refugees’ under the terms of the Geneva Convention by the European governments: a status which grants considerable rights and protection. This number is quite lower with an average of around 40.000 per year (in the EU+ as a whole) which makes for less than half-a-million in total for the 12 years between 2001 and 2012. While the overall recognition rate remains between 7% and 14%, there is considerable variation between the different European states both in the share from the asylum flows they receive, and in the national asylum recognition rates.

Who takes the brunt of the asylum burden?
Both the asylum flows and the recognition rates are in fact distributed highly unequally across the continent, and in a way that cannot be completely accounted for by the wealth of destination countries, former (colonial) ties between asylum sources and destinations, nor geographical distance. To compare the shares of the total European pool of asylum applications and recognitions that a destination country gets, I create the so-called ‘burden coefficient’. The ‘burden coefficient’ compares the actual share of asylum applications a country received in a year to its ‘fair’ share which is defined as its relative share of the annual  total EU+ GDP. Simply put, if a country accounts for 10% of the European GDP, it would have been expected to receive 10% of all asylum applications filed in Europe that year. Taking account of GDP adjusts the raw asylum application shares in view of the expectation that richer and more populous countries should bear a proportionally higher share of the total European asylum ‘burden’ than poorer and smaller states.

asylum_applications_burden

Figure 2 shows the (logged) burden coefficient for asylum application shares for each EU+ country, averaged over the period 2010-2012. The solid line at zero indicates an asylum applications share perfectly proportional to a  country’s GDP share (a ‘fair’ burden). Countries with positive values receive a higher share of all applications than implied by their GDP level, and countries with negative values receive a lower than their implied share. (The dotted lines show where a country that is doing twice as much / twice as little as expected would be). Clearly, Spain, Portugal, Italy and many (but not all) of the East European countries underdeliver while Cyprus, Malta, Greece, and several West European states (notably Sweden, Belgium, and Norway) take a disproportionately high  share of the total pool of asylum applications filed in Europe over the last few years. Note that these comparisons already take into account (correct for) the fact that most of the Southern and Eastern European countries are poorer (have lower GDP) than the ones in the Western and Northern parts of the continent.

asylum_recognitions_burden

The picture does not change much when we focus on actual asylum recognitions (under the terms of the Geneva Convention) instead of applications. Figure 3 shows the burden coefficient (again averaged over 2010-2012) for full status refugee recognitions in Europe. The country ranking is similar with a few important exception – Greece grants much fewer asylum recognitions than expected even after we account for the state of its economy; Austria and Switzerland join the ranks of states which do much more than their implied share; and, sadly, many more countries in fact underdeliver when it comes to full refugee status grants. (Note that some states offer alternative protection to those denied the full ‘Geneva Convention’ status but the forms and level of this protection differs significantly across the continent).

Are asylum application shares responsive to the recognition rate?
Given these rather significant discrepancies across Europe in how many asylum applications countries get, and how much protection they offer, it is natural to ask whether the applications shares and the recognition rates are in fact related. Do asylum seekers flock at the gates of the European states which are most generous in their recognition policy? Do low recognition rates deter potential refugees from applying in certain countries? Can the strictness of asylum policy be an effective policy tool shaping future application flows? A comprehensive statistical analysis shows that while application shares and recognition rates are associated, their responsiveness to each other is rather weak. Simply put, manipulating the recognition rates is unlikely to have big practical effects on the asylum application share a country receives, and changes in the applications rates only weakly affect state recognition rates. The details of the analysis are rather technical and can be found here, but a dynamic visualization can help illustrate the patterns.

The dynamic interactive chart linked here shows the relationship between asylum applications and asylum recognition rates for each EU+ country over the last 12 years (the chart cannot be embedded in this post due to WordPress policy, but there is a screenshot below). When you press ‘Play’ each dot traces the experience of one country over time. You can choose to observe all, select a single state to focus upon, or tick a couple to compare their experiences.

dynamic-asylum-1

A movement of a dot (and the trace in leaves) in a horizontal direction means that the number of asylum applications received by a country increases while the recognition rates remains the same. Similarly, a vertical move implies a change in the recognition rate but a stable asylum application flow. A trajectory that follows a diagonal suggests a link between applications and recognition rates.

When paused, the state of the chart at each year shows the cross-sectional association between applications and recognition rates: it is easy to see that there is a (rather stable) weakly-strong positive relationship. But the trajectories of individual countries over time do not suggest that there is a temporal link between the two aspects of asylum policy for particular countries. For example, in the UK between 2001 and 2004 both the recognition rates and the applications fall, which would suggest strong responsiveness, but then the recognition rate moves up from 4% to almost 30% without any significant increase in applications. The trajectory of Denmark (try it out) exhibits something close to a dynamic link with rates depressing applications initially but then when they rise again, applications seem to pick up as well. Of course, asylum flows are driven by many other factors as well, so while suggestive, the patterns in the chart should be interpreted with care.

dynamic-asylum-2

More comprehensive analyses of asylum policy in Europe addressing these questions and more are available in my published articles accessible here and here. The original data comes from the UNHCR annual reports. The dynamic chart is generated using Google Chart Tools through the googleVis library in R, you can find the code here. I found it useful to generate a simple version, adjust the settings manually, and then copy the final settings via the Google Chart’s Advanced Panel back to R.

Bureaucrats as Policy-makers

Everyone loves bitching about bureaucrats but few know what it is exactly that they do. Ed Page‘s new book ‘Policies without Politicians’ provides plenty of insights. As I mention at the end of this book review, everyone who theorizes or criticizes bureaucrats should read the book as a reality check. A shorter version of the review is forthcoming in West European Politics later this year.
***

This book is about the making of decrees such as the Alcohol Disorder Zones in the UK, Salmon critical habitats in the US, Horse Medicines in the EU and Women’s Organizations in Sweden. If you suspect these issues are rather prosaic, you are not alone. And this is precisely the point. This book is about the making of policies in the absence of sustained attention by politicians. It is a study of how bureaucrats make rules when mostly left to their own devices. It is an exploration into the nature and limits of bureaucratic discretion to regulate our lives.

The main conclusion, based on an analysis of 58 issues in six political systems, is that the freedom enjoyed by civil servants and their insulation from political control are in practice severely limited if not completely illusory, even when it comes to the relatively minor issues discussed in the book. Admittedly, this is a rather prosaic conclusion as well, but one that is comforting, timely andimportant. It is comforting to the extent that it dispels the popular myth of the faceless bureaucrats controlling our lives. It is timely because theories of policy-making and politico-administrative relations have became increasingly preoccupied with issues like bureaucratic drift, shirking, delegation costs, and the like with little evidence that these actually matter in real life. Finally, the conclusion is important in
view of the continuing tendency of political science to ignore the pedestrian reality of everyday policy making which although lacking the suspense of high politics comprises the bulk of the activities of states and public organizations.

The book contains an introduction, six empirical chapters covering policy-making in France, Britain, Germany, Sweden, the United States, and the European Union, and a conclusion. In this review I will follow the opposite route by first summarizing part of the generalizations offered in the last part, then focusing on some of the country-level insights, and finally commenting on the approach of the book.

Studying the origin and passage of a moderately large sample of secondary legislation (decrees), Edward Page concludes that politicians generally get their way even if their attention towards the issues is sporadic. Bureaucrats anticipate the preferences of their political masters and adjust the text of the decrees to the politicians’ explicit or assumed wishes. Moreover, bureaucratic discretion is severely constrained by precedent, existing legal codes, and procedural rules for the preparation of legislation, in addition to the need to anticipate and avoid political vetoes. And if for most of the decrees political direction is passive, there is a tendency for the relatively important ones to be developed under direct
and active political guidance.Contrary to theoretical expectations, the technical and scientific character of many of the issues is not sufficient to exclude political involvement (p.153). Also running against some popular theoretical ideas based on principal-agent modeling is the observation that it was never an ‘alarm’ set off by interest groups (p.151) that brought political attention to an issue. Again, bureaucrats tend to detectand anticipate potential conflicts and solve them before they offer the decrees for final approval. But it
is internal norms rather than external scrutiny or outside interests that are most important in keeping the bureaucrats in check, according to the book (p.165).

Politicians appear to be most often involved in the legitimation of decrees, but that does not mean bureaucrats have a free hand during the agenda-setting stage. Not only did many decrees offer no scope for policy deliberation at all, but in most cases there was almost no scope for choice whether to introduce the proposal in the first place: proposals often followed automatically from prior commitments in primary legislation, the need to update, codify, or clean up existing rules, or the obligation to apply international norms and agreements. In this context the author is right to question the relevance of theoretical concerns like bureaucratic drift and shirking, and ponder what would selfinterested
bureaucratic preferences even look like with regard to many of the policy issues discussed in the book (p.160). If one looks for the influence of civil servants, it is not to be found in the supposedly unconstrained discretion they enjoy in pushing their own agendas or preferences, but in the routinization, regularization and adjustment of policy they perform (pp.168-170).

These general patterns seem to be influenced by the national institutional context (pp.155-158) and vary to some extent across the six political systems studied. Sweden appears to be the place where politicians are most likely to get involved in the preparation of decrees even when one would expects them not to. On the other end of the spectrum, the UK and Germany exhibit the lowest degree of direct political involvement. In the German case, this stems from the fact that potential conflicts are solved in different institutional arenas before the drafting of the decrees had even started. As for the UK, the book posits a ‘general reluctance among politicians to get directly and actively involved in the activity of
rule-making ‘ (p.157). A surprising degree of political involvement (mostly as agenda selectors) is found in the generally pluralist American system, in addition to the continual importance of the agency as the central locus of organizational identity for American bureaucrats. The French system is found to be unexpectedly ‘as close to interest group corporatism as it is to the traditional aloof ‘strong state”’ (p.44).

But it is the chapter on the European Union that most strongly contradicts the popular perceptions and received common, if not academic, wisdom. Page is clear that ‘the role of Commission bureaucrats as [policy] initiators was highly limited’ (p.128), Commissioners often get directly involved, and there is very little scope for independent action. Far from enjoying a bureaucrat’s paradise, civil servants in the European Union appear to have very little substantial autonomy and influence.

Although the synchronic comparisons between the six political systems and the diachronic
comparisons with previous academic accounts suggest intriguing patterns, the book can pursue them only as far. The study is unapologetically inductive, there is little effort to systematize the empirical mess of real-word policy-making into variables, and the case selection is driven primarily by pragmatic reasons. While this serves the exploratory objectives of the book well, it also posits limits on the inferences and generalizations one can make. Since the sample of issues (decrees) is not (intended to be) representative it is difficult to judge whether the case studies provide evidence for genuine change in national policy-making styles (e.g. France, the US), or for systematic differences between  countries (e.g. Sweden vs. the UK). Since the decrees researched differ across the six political systems, the question why certain issues are left for bureaucratic policy-making (decrees) in one country but get in the social and political prime-time in others is left answered. Furthermore, by selecting only cases which eventually resulted in a decree, the book might have overlooked potentially interesting cases where (political) conflict stopped the development of policy in its tracks.

These points are as much suggestions for future research as they are criticisms of the current volume. The book is quite clear about its own limitations deliberately positioning itself as an inductive exploration. And it achieves its purpose rather well. As the author notes, it is difficult to produce a good book describing cases which are dull and boring by definition, but, although not gripping, the text manages to provide just enough detail and institutional context to keep the reader interested. In fact, the short presentations of the six policy-making systems contained in each of the country chapters make the book suitable for primary or complementary reading for academic courses on comparative bureaucracy and comparative public policy. But above all, the book should be required reading, and a
reality check, for all those who theorize and criticize bureaucracy and bureaucrats for their alleged discretion in regulating our lives.

Co-decision and decision-making speed in the EU

Our paper (with Anne Rasmussen) on the influence of early agreements (trilogues) on the speed of decision making in the EU has just been published by the European Integration Online Papers (EIoP). The abstract is below. Anne blogged about the findings here.  

Abstract: The increased use of early agreements in the EU co-decision procedure raises the concern that intra and inter-institutional political debate is sacrificed for the sake of efficiency. We investigate the effect of early agreements (trilogues) on the time it takes for legislation to be negotiated during the first reading of co-decision. We find that the first reading negotiations of trilogues on salient legislation take longer than first readings of similar files reconciled at second and third reading. First readings of early agreements also appear to last longer when considering all co-decision files submitted to the 5th and 6th European Parliaments, but the effect is masked by a general increase in first reading duration after 2004. We conclude that even if early agreements restrict access of certain actors to decision making, they allow for more time for substantive debate at the first reading stage than similar files reconciled later in the legislative process.

By the way, let me use the occasion to congratulate EIoP for being one of the very few free  and rigorously peer-reviewed, SSCI-indexed, journals. All articles are available online without a subscription and without a registration. While many people talk against the gated and hugely expensive academic journals, very few authors actually support the free alternatives by submitting to and reviewing for them.

Diffusion of smoking bans in Europe

My paper on the diffusion of smoking bans in Europe has been accepted in Public Administration. It probably won’t be published until next year so here is a link to the pre-print and a graph of two of the important results of the paper: the probability of enactment of a more comprehensive (full) smoking ban increases with lower levels of tobacco producton and with rising levels of public support for smoking restrictions:

  And the abstract:

Policy Making Beyond Political Ideology: The Adoption of Smoking Bans in Europe

Policy making is embedded in politics, but an increasing number of issues, like obesity, tobacco control, or road safety, do not map well on the major dimensions of political conflict. This article analyzes the enactment of restrictions on smoking in bars and restaurants in 29 European countries – a conflictual issue which does not fit easily traditional party ideologies. Indeed, the comparative empirical analyses demonstrate that government ideological positions are not associated with the strictness and the timing of adoption of the smoking bans. On the other hand, economic factors like the scale of tobacco production in a country, smoking prevalence in society and public support for tough anti-smoking policy are all significantly related to the time it takes for a country to adopt smoking bans, and to the comprehensiveness and enforcement of these restrictions. In addition, horizontal policy diffusion is strongly implicated in the pattern of policy adoptions.  

New tool for discourse network analysis

EJPR has just published an article introducing a new tool for ‘discourse network analysis’. Using the tool, you can measure and visualize political discourses and the networks of actors affiliated to each discourse. One can study the actor congruence networks (based on the number of statements actors share), concept congruence networks (based on whether statements are used by an actor in the same way) and trace the evolution of both over time.

Here is a graph taken from the paper which illustrates the actor congruence networks for the issue of software patents in the EU (click to enlarge):

The discourse networks analysis tool is free and available from the website of Philip Leifeld, one of the co-authors of the article. I can’t wait to get my hands on the program and try it out for myself. The tool promises to be an interesting alternative to evolutionary factor analysis – another new method for studying policy frames and discourses that I recently discussed – with the added benefit of being able to present actors and frames in an integrated analysis.  

Here is the abstract of the EJPR article (there are more resources at this website):

In 2005, the European Parliament rejected the directive ‘on the patentability of computer-implemented inventions’, which had been drafted and supported by the European Commission, the Council and well-organised industrial interests, with an overwhelming majority. In this unusual case, a coalition of opponents of software patents prevailed over a strong industry-led coalition. In this article, an explanation is developed based on political discourse showing that two stable and distinct discourse coalitions can be identified and measured over time. The apparently weak coalition of software patent opponents shows typical properties of a hegemonic discourse coalition. It presents itself as being more coherent, employs a better-integrated set of frames and dominates key economic arguments, while the proponents of software patents are not as well-organised. This configuration of the discourse gave leeway for an alternative course of political action by the European Parliament. The notion of discourse coalitions and related structural features of the discourse are operationalised by drawing on social network analysis. More specifically, discourse network analysis is introduced as a new methodology for the study of policy debates. The approach is capable of measuring empirical discourses both statically and in a longitudinal way, and is compatible with the policy network approach.

Compiling government positions from the Manifesto Project data with R

****N.B. I have updated the function in February 2014 to makes use of the latest Manifesto data. See for details here.***

The Manifesto Project (former Manifesto Research Group, Comparative Manifestos Project) has assembled a database of ‘quantitative content analyses of parties’ election programs from more than 50 countries covering all free, democratic elections since 1945′ and is freely accessible online. The data, however, is available only at the party, and not at the government (cabinet) level. In order to automate  the process of extracting government positions from the Manifesto data, I wrote a simple R function which combines the party-level Manifesto data with the data on government compositions from the ParlGov database. The function manifesto.position() produces a data frame with the country, the time period, the government position of interest, and an index (id) variable. You can get the data either at a monthly or yearly period of aggregation, specify the start and the end dates, and get the data in ‘long’ or ‘wide’ format.

Here is how it works: First, you would need R up and running (with the ‘ggplot2‘ library installed). Second, you need the original data on party positions and on government compositions, and this script to merge them. Alternatively, you can download (or source) directly the resulting merged dataset here. Third, you need to source the file containing the functions.

Here are a few examples of the function in action:

####
### 1. Load the data file from the working directory or from the URL (default)
#cabinets<-read.table ('cabinets.txt', as.is=TRUE)
cabinets<-read.table ('http://www.dimiter.eu/Data_files/cabinets/cabinets.txt', as.is=TRUE)

### 2. Load the functions from the working directory or from the URL (default)
#source('government position extraction functions.R')
source('http://www.dimiter.eu/Data_files/cabinets/government%20position%20extraction%20functions.R')

### Use of manifesto.position(x, weighted=TRUE, long=TRUE, period='year', start=1945, end=2010)
### Inputs:
###         x [the name of the Manifesto item]
###         weighted  [weighted mean of the government position or a simple unweighted mean]
###         period    [year (default)  or month - time period for which the position is extracted]
###         long      [long (default)  or wide version of the output data]
###         start     [starting year for the extraction; 1945 is default]
###         end       [end year of the extraction; 2010 is default]
### Output: A data frame with four columns - State, Year (Year.month), position [the actual position], id [Year.State(Year.month.State)]
### For details see the sourced file above

### Examples
##  1. Extract the left/right positions
lr<-manifesto.position('rile')
summary(lr)

## 2. Exatract the unweighted International peace position from 1980 until 1999
intp<-manifesto.position('intpeace', weighted=F, start=1980, end=1999)
hist(intp$position)

## 3. Exatract the weighted Welfare position from 1980 until 1999 in a wide, rather than long shape - states are rows and years are colunms
welfare<-manifesto.position('welfare', long=F, start=1980, end=1999)
welfareT<-t(welfare) ##this would make the countries columns and the years rows.

## 4. Left/right on a monthly basis from 1980 till 1990
lrm<-manifesto.position('rile', period='month', start=1980, end=1990)

I hope you find the function useful. Feel free to e-mail any suggestions, remarks, reports on bugs, etc. If you use the function and the data, don’t forget to acknowledge the work of the people who collected the Manifestos and who compiled the ParlGov database.

Governing by Polls

The study of policy responsiveness to public opinion is blossoming and propagating. Work published over the last two years includes the 2010 book by Stuart Soroka and Chris Wlezien (Canada, US and the UK), this paper by Sattler, Brandt, and Freeeman on the UK,  this paper on Denmark, my own article on the EU, Roberts and Kim’s work on post-Communist Europe, etc.  The latest edition to the literature is this article by Jeffrey Lax and Justin Phillips from Columbia University (forthcoming in AJPS).

“The Democratic Deficit in the States” takes a cross-sectional rather than a dynamic (time series) perspective and analyzes both responsiveness  (correlation)  and congruence between policy outcomes and public opinion in the US states for eight policies. In short, there is a high degree of responsiveness but far from perfect congruence between majority opinion and policy. More salient policies fair better, and having powerful interest groups on your side helps. Altogether, this is an interesting and important study that adds yet another piece to our understanding of policy responsiveness.

What starts to worry me, however, is that the normative implications of the policy responsiveness literature are too often taken for granted. Lax and Phillips seem to equate the lack of correspondence between public opinion and policy to democratic deficit(similarly, Sattler, Brandt and Freeman speak of ‘democratic accountability’). But there is quite a gap between the fact the a policy contradicts the majority of public opinion and the pronouncement of democratic failure. And we need to start unpacking the normative implications of the (lack of) policy responsiveness. 

Of course, at a very general level no political system can be democratic unless there is dynamic responsiveness and broad correspondence between the wishes of the public and what government does. But can we equate congruence of policy with public opinion with democracy? I don’t think so. Precise responsiveness and congruence are neither necessary nor sufficient for democratic policy making. Why?

First and foremost, public opinion as such does not exist. One doesn’t need to embrace a radical post-modern position to admit that the numbers we love to crunch in studies of policy responsiveness are, at best, imperfect (snapshot) estimates of a fluid social construct. It is not only that estimates of aggregate public opinion are subject to the usual measurement problems. It has been shown times and again that the answers we get from public surveys are sensitive to the precise wording, form, and  context of the questions (see George Bishop’s ‘The Illusion of Public Opinion’ for an overview). The questions themselves are often vague and imprecise. Polls will elicit responses even when the people have no meaningful opinion towards the issue (opinions will be regularly given even on fictitious issues). The availability bias is often a problem, especially in surveys of the ‘most important problem’ (open vs. close forms of the question).

A second problem is that public opinion as portrayed by mass surveys need not be the same as the opinion of a group of people after they (1) have been given relevant information about the issue, (2) have been allowed ample time to think about it, and (3) have had the opportunity to deliberate about it (on deliberative polls which come with their own set of problems see James Fishkin). People know astoundingly little about current policies even when they are personally affected by them (here). Do we expect congruence and responsiveness between policy and public opinion as given over the telephone after a modicum of brain activity, or policy and public opinion as it would have been if people made informed decisions with the common good in mind?

The third problem is that public opinion is expressed on various issues presented in isolation. I can very well support an increase in spending on defense, education, and health, and a decrease in the overall state budget at the very same time.  My opinion and preferences need not be consistent but policies need to be. The problem is compounded by the possibility of preference cycles in aggregate public opinion. Even if individual opinions are rational and well-behaved, preference cycles in aggregate public opinion cannot be ruled out.

There is some unintended irony in Stimson et al. designating the aggregate of attitudes and opinions they construct the ‘policy mood’ of the public. Normatively speaking, do we really expect policy to respond to the mood of the public with all the irrationality, instability and caprice that a mood implies? All in all, the lack of perfect temporal and spatial correspondence between public opinion and policy cannot be interpreted directly as a sign of democratic deficit and failure. Political institutions translating mass preferences into policy exist for a reason (well, a number of reasons, including preference aggregation, deliberation, and inducing stability).

The other side of the same coin is that responsiveness is not sufficient for democracy. The fact that a government follows closely majority opinion as expressed in the polls and adjusts policy accordingly cannot be a substitute for a democratic policy making process. This is especially clear in my own analysis of the EU: although I find that aggregate legislative production closely follows the ebbs and flows in public support for the EU during the 1970s, 1980s, and early 1990s this cannot dispel our misgivings about the democratic deficit of the EU during this period – the polls are not a substitute for elections, representation, and accountability.

The lack of sufficient reflection on the democratic implications of the (lack of ) policy responsiveness is especially worrying in view of the tendency (identified on the basis of my subjective reading of the political process in several European states) of more and more reference to and reliance on ‘instant’ polls in making policy. The increased availability and speed of delivery of ‘representative’ public opinion polls lures politicians into dancing to the tune of public opinion on every occasion. Sensible policies are abandoned if the poll numbers are not right (e.g. second hand smoking restrictions, see here), and retrogressive policies are enacted if the percentage of public support is high enough. But government by polls is only one step removed from the government by mobs. Politicians should sometimes have different policy opinions than the public and they should have the courage to pursue these opinions in the face of (temporary and latent) opposition by the citizens. Meanwhile, social science has the important task to uncover when and how policy responsivness and congruence works. But I see no need to inflate and oversell the normative implications of the research.