get_lender_sentiment: Get Mortgage Lender Sentiment Survey data

In saadaslam/fannieapi: A R interface for accessing The Exchange, which is Fannie Mae's public API

Description

Get Mortgage Lender Sentiment Survey data

Usage

get_lender_sentiment()

Details

The questionnaire for the mortgage lender sentiment survey is available on the Fannie Mae website. Available questions in the survey data are:

• 6 – Over the past three months, apart from normal seasonal variation, did your firm<e2><80><99>s consumer demand for single-family purchase mortgages go up, go down, or stay the same?

  • Part a refers to GSE Eligible mortgages

  • Part b refers to Non-GSE Eligible mortgages

  • Part c refers to government (i.e. Federal Housing Administration or Department of Veteran Affairs) mortgages.

• 10 – Over the past three months, apart from normal seasonal variation, did your firm<e2><80><99>s consumer demand for single-family refinance mortgages go up, go down, or stay the same?

  • Part a refers to GSE Eligible mortgages

  • Part b refers to Non-GSE Eligible mortgages

  • Part c refers to government (i.e. Federal Housing Administration or Department of Veteran Affairs) mortgages.

• 14 – Over the next three months, apart from normal seasonal variation, do you expect your firm<e2><80><99>s consumer demand for single-family purchase mortgages to go up, go down, or stay the same?

  • Part a refers to GSE Eligible mortgages

  • Part b refers to Non-GSE Eligible mortgages

  • Part c refers to government (i.e. Federal Housing Administration or Department of Veteran Affairs) mortgages.

• 18 – Over the next three months, apart from normal seasonal variation, do you expect your firm<e2><80><99>s consumer demand for single-family refinance mortgages to go up, go down, or stay the same?

  • Part a refers to GSE Eligible mortgages

  • Part b refers to Non-GSE Eligible mortgages

  • Part c refers to government (i.e. Federal Housing Administration or Department of Veteran Affairs) mortgages.

• 22 – Over the next three months, how much do you expect your firm's profit margin to change for its single-family mortgage production?

• 27 – Over the past three months, how did your firm<e2><80><99>s credit standards for approving consumer applications for mortgage loans change (across both purchase mortgages and refinance mortgages)? Please answer for GSE Eligible mortgages, Non-GSE Eligible mortgages, and Government mortgages.

  • Part a refers to GSE Eligible mortgages

  • Part b refers to Non-GSE Eligible mortgages

  • Part c refers to government (i.e. Federal Housing Administration or Department of Veteran Affairs) mortgages.

  • Note that "up" refers to loosening of credit standards and "down" refers to tightening of credit standards.

• 31 – Over the next three months, how did your firm<e2><80><99>s credit standards for approving consumer applications for mortgage loans change (across both purchase mortgages and refinance mortgages)? Please answer for GSE Eligible mortgages, Non-GSE Eligible mortgages, and Government mortgages.

  • Part a refers to GSE Eligible mortgages

  • Part b refers to Non-GSE Eligible mortgages

  • Part c refers to government (i.e. Federal Housing Administration or Department of Veteran Affairs) mortgages.

  • Note that "up" refers to loosening of credit standards and "down" refers to tightening of credit standards.

Value

A tbl_df containing the following columns

• question – The question number on the survey

• lender_catg – A category defining the lender group.

• survey_date – The date of the survey

• percent_net_up – This is equivalent to percent_went_up minus percent_went_down

• percent_stays_the_same – The proportion of lenders that answered the question as "stays the same."

• percent_went_down – The proportion of lenders that answered the question as "went down."

• percent_went_up – The proportion of lenders that answered the question as "went up."

See Also

lender_sentiment_questions

Examples

result <- get_lender_sentiment()

saadaslam/fannieapi documentation built on May 16, 2019, 9:11 p.m.