Working in Excel

Part 11.1 Summarizing the data

We will be using data collected from an internet survey sponsored by the German government.

First, download the survey data and documentation:

  1. While contingent valuation methods can be useful, they also have shortcomings. Read Section 5 of the paper ‘Introduction to economic valuation methods’ (pages 16–19), and explain which limitations you think apply particularly to the survey we are looking at.
Likert scale
A numerical scale (usually ranging from 1–5 or 1–7) used to measure attitudes or opinions, with each number representing the individual’s level of agreement or disagreement with a particular statement.

Before comparing between question types, we will first compare the people assigned to each question type to see if they are similar in demographic characteristics and attitudes towards related topics (such as beliefs about climate change and the need for government intervention). Attitudes were assessed using a 1–5 Likert scale, where 1 = strongly disagree, and 5 = strongly agree.

  1. Re-code or create the variables as specified:
Original value New value
1 48
2 72
3 84
4 108
5 156
6 192
7 252
8 324
9 432
10 540
11 720
12 960
13 1,200
14 1,440

WTP survey categories (original value) and euro amounts (new value).

Figure 11.1 WTP survey categories (original value) and euro amounts (new value).

  1. Create the following indices, giving them an appropriate name in your spreadsheet (make sure to use the reverse-coded variable where relevant):
Cronbach’s alpha
A measure used to assess the extent to which a set of items is a reliable or consistent measure of a concept. This measure ranges from 0–1, with 0 meaning that all of the items are independent of one another, and 1 meaning that all of the items are perfectly correlated with each other.

When creating indices, we may be interested to see if each item used in the index measures the same underlying variable of interest (known as reliability or consistency). There are two common ways to assess reliability: either look at the correlation between items in the index, or use a summary measure called Cronbach’s alpha (this measure is used in the social sciences).

Cronbach’s alpha is a way to summarize the correlations between many variables, and ranges from 0 to 1, with 0 meaning that all of the items are independent of one another, and 1 meaning that all of the items are perfectly correlated with each other. While higher values of this measure indicate that the items are closely related and therefore measure the same concept, with values that are very close to 1 (or 1) we could be concerned that our index contains redundant items (for example, two items that tell us the same information, so we would only want to use one or the other, but not both). You can read more about this in the paper ‘Using and interpreting Cronbach’s Alpha’.

  1. Calculate correlation coefficients and interpret Cronbach’s alpha:
  scepticism_2 scepticism_6 scepticism_7
scepticism_2 1
scepticism_6   1
scepticism_7     1

Correlation table for items in Question 3(a).

Figure 11.2 Correlation table for items in Question 3(a).

Now we will compare characteristics of people in the dichotomous choice (DC) group and two-way payment ladder (TWPL) group (the variable ‘abst_format’ indicates which group an individual belongs to). Since the groups are of different sizes, we will use percentages instead of frequencies.

  1. For each group, create separate tables to summarize the distribution of the following variables:

    • gender (‘sex’)
    • age (‘age’)
    • number of children (‘kids_nr’)
    • household net income per month in euros (‘hhnetinc’)
    • membership in environmental organization (‘member’)
    • highest educational attainment (‘education’).

    Without doing formal statistical tests, do the two groups of individuals (DC and TWPL) look similar in demographic characteristics?

  1. Create summary tables as shown in Figure 11.3 for each index you created in Question 3. Without doing formal statistical tests, do the two groups of individuals look similar in the attitudes specified?
  Mean Standard deviation Min Max
DC format        
TWPL format        

Summary table for indices.

Figure 11.3 Summary table for indices.

Part 11.2 Comparing willingness to pay across methods and individual characteristics

Before comparing WTP across question formats, we will summarize the distribution of WTP within each question format.

  1. For individuals who answered the TWPL question:
  1. For individuals who answered the DC question:
  1. Compare the mean and median WTP under both question formats:
Format Mean Standard deviation Number of observations
DC      
TWPL      

Summary table for WTP.

Figure 11.4 Summary table for WTP.