are willing to accept an authoritarian government under certain circumstances or whether they believe authoritarian governments are never acceptable.

# **Regression methods**

We estimate ordered probit models with fixed effects for countries and robust t-statistics.<sup>12</sup> Rather than presenting regression tables with p-values, we discuss the regression results using predicted probabilities and first differences of attitudes towards neighbors. King (1989) introduced the concept of first differences as distinct from first differences of regressions. First differences and predicted probabilities provide a sense of the size of the effect of variables for quantities of interest. In an ordered probit equation, first differences are estimates of how much the predicted probability would change in response to a particular change in an explanatory variable, while holding the other variables in the equation constant.<sup>13</sup> We present first differences with confidence intervals reflecting the estimation and fundamental uncertainty of the point predictions. To calculate the confidence intervals, we follow the algorithm presented by King (2000) and repeat the algorithm 10,000 times. We graphically present the first differences and the uncertainty around these estimates in coefficient plots (see Figures 4 through 6). In these plots, the first differences are reflected as dark circles and the horizontal lines represent the simulated 95% confidence intervals. For example, Figure 4 shows that moving from Sweden to Moldova corresponds to a percentage point increase of 19.1 in the probability that one is willing to tolerate living next to the poor or people at different lifecycle stages.

In the analyses that follow, we calculate first differences for hypothetical scenarios for the average respondent from Sweden compared to Moldova (cluster 1), France compared to Russia (cluster 2) and Croatia compared to Turkey (cluster 3). We calculate first differences that the average respondent will have completely tolerant attitudes (the first category in the ordered probit model) and completely intolerant attitudes (the last category in the ordered probit model).

# **Regression results**

> 12 Technically, the dataset used for this paper has a multilevel structure; individuals are nested within primary sampling units (PSUs), which are nested within countries. The PSUs are the smallest, well-defined geographic units for which reliable population data are available and they tend to be socially homogenous, thereby producing highly clustered data. In most countries, these will be Census Enumeration Areas. Ideally, we should be estimating multilevel ordered logits. Because of the difficulties in implementing this type of model, we estimated ordered logistic models with fixed effects for countries and robust t-statistics.

13 First differences are calculated by holding all variables at their mean and setting one variable first to a low value and next to a high value. We then use an algorithm to calculate the change in the predicted probability with simulated confidence intervals (to give us an estimate of uncertainty around the predicted probability) - the first difference. For example, we calculate the predicted probability that the average respondent from Sweden who is 18 years old won't mind living next to people with specific behaviors. We then calculate the predicted probability that the average respondent from Sweden who is 54 years old won't mind living next to people with specific behaviors. The difference in the two probabilities is the first difference. A hypothetical value of 0.075 can be interpreted as follows: The difference in the predicted probability that an 18 year old versus a 54 year old from Sweden will tolerate living next to people with various different behaviors is 7.5 percentage points. Effect sizes of less than 5 percentage points are fairly small.

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