Empirical Project 11 Working in Excel

Part 11.1 Summarizing the data

Learning objectives for this part

  • construct indices to measure attitudes or opinions
  • use Cronbach’s alpha to assess indices for internal consistency
  • practise recoding and creating new variables.

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. You may also find it useful to look at Table 2 of that paper, which compares stated-preference with revealed-preference methods.

Before comparing between question formats (dichotomous choice (DC) and two-way payment ladder (TWPL)), we will first compare the people assigned to each question format 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). If the groups are vastly dissimilar then any observed differences in answers between the groups might be due to differences in attitudes and/or demographics rather than the question format.

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.

Attitudes were assessed using a 1–5 Likert scale, where 1 = strongly disagree, and 5 = strongly agree. The way the questions were asked was not consistent, so an answer of ‘strongly agree’ might mean high climate change skepticism for one question, but low skepticism for another question. In order to combine these questions into an index we need to recode (in this case, reverse-code) some of the variables.

  1. Recode 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

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). We will be calculating and interpreting both of these measures.

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:
  exaggeration not.human.activity no.evidence
exaggeration 1
not.human.activity   1
no.evidence     1

Figure 11.2 Correlation table for survey items on climate change scepticism: Climate change is exaggerated (exaggeration), Human activity is not the main cause of climate change (not.human.activity), No evidence of global warming (no.evidence).

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 (DC and TWPL), create tables to summarize the distribution of the following variables (a separate table for each variable):

    • 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’).

    For help on creating tables, see Excel walk-through 3.1. Using the tables you have created, and without doing formal calculations, discuss any similarities/differences in demographic characteristics between the two groups.

  1. Create a separate summary table as shown in Figure 11.3 for each of the three indices you created in Question 3. Without doing formal calculations, do the two groups of individuals look similar in the attitudes specified?
  Mean Standard deviation Min Max
DC format        
TWPL format        

Figure 11.3 Summary table for indices.

Part 11.2 Comparing willingness to pay across methods and individual characteristics

Learning objectives for this part

  • compare survey measures of willingness to pay.

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      

Figure 11.4 Summary table for WTP.