Decision Maker Panel Key Charts Nick Bloom Stanford

Decision Maker Panel: Key Charts Nick Bloom (Stanford), Phil Bunn (Bank of England), Scarlet Chen (Stanford) Paul Mizen (Nottingham), Pawel Smietanka (Bank of England), Jenny Lam (Bank of England) January 2020 Disclaimer: Any opinions and conclusions expressed herein are those of the authors and do not necessarily represent the views of the Bank of England or its Committees.

Brexit Uncertainty index Source: Decision Maker Panel and authors’ calculations. Notes: The results are based on the question ‘How much has the result of the EU referendum affected the level of uncertainty affecting your business? ’. The line shows the percentage of respondents who view Brexit as “their top” or “one of their top three” sources of uncertainty. The remaining businesses reported Brexit to be “one of many” or “not an important” source of uncertainty for their business. Before August 2018, when the question about uncertainty was not asked every month, missing values are interpolated. All values are weighted.

Brexit as a source of uncertainty Source: Decision Maker Panel and authors’ calculations. Notes: The results are based on the question ‘How much has the result of the EU referendum affected the level of uncertainty affecting your business ? ’ All values are weighted.

Brexit uncertainty by industry Wholesale & Retail Manufacturing Finance & Insurance Construction Accom & Food Prof & Scientific Real Estate Admin & Support Transport & Storage Other Production Info & Comms Other Services Health All industries 0 10 20 30 40 50 Brexit uncertainty index (0 - 100 scale) 60

Brexit uncertainty by firm size 10 - 49 employees 100 - 249 employees 50 - 99 employees 250+ employees All firms 0 10 20 30 40 50 Brexit uncertainty index (0 - 100 scale)

Brexit exposure and uncertainty Source: Bureau van Dijk FAME dataset, Decision Maker Panel and authors’ calculations. Notes: All EU exposure measures are for 2016 H 1, just before the Brexit referendum. Charts show the average uncertainty per firm reported in the three years after the referendum. Missing values for uncertainty in a given year are imputed from a regression using time and firm fixed effects. See footnote to Figure 1 for definition of the Brexit Uncertainty Index (BUI).

Productivity and Brexit uncertainty Source: Bureau van Dijk FAME dataset, Decision Maker Panel and authors’ calculations. Notes: See footnote to Figure 1 for definition of the Brexit Uncertainty Index (BUI) and the footnote to Figure 3 f or definition of productivity.

Sources of Brexit uncertainty Percentage of respondents affected by Brexit uncertainty 50 Largest current source of Brexit uncertainty Top 3 but not largest current source of Brexit uncertainty 40 30 20 10 0 Labour availability Regulation Demand Customs Supply chains Source: Decision Maker Panel and authors’ calculations. Notes: The results are based on the question ‘How important are the following factors as sources of Brexit-related uncertainty for your business at present? Please select one option for each [from Not important/One of many/One of top 2 or 3 but not largest source/Largest current source]: Uncertainty about demand for your goods/services; Uncertainty about the availability of labour; Uncertainty about supply chains/availability of inputs other than labour; Uncertainty about regulation; Uncertainty about customs arrangements/tariffs’. Data were collected between February and April 2019. All values are weighted.

Expected date when Brexit-related uncertainty will be resolved Percentage of respondents 70 During 2020 60 50 40 2021 onwards 30 20 By end 2019 10 0 Feb 2019 Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan 2020 Source: Decision Maker Panel and authors’ calculations. Notes: The results are based on the question ‘When do you think it is most likely that the Brexit-related uncertainty facing your business will be resolved? ’. Data were collected between February 2019 and January 2020. All values are weighted.

Year when the UK is expected to leave the EU Average probability, per cent 35 30 25 20 15 10 5 0 2020 with no trade deal agreed 2020 with a trade deal agreed 2021 with no trade deal agreed 2021 with a trade deal agreed 2022+ Never Anticipated time of leaving the EU Source: Decision Maker Panel and authors’ calculations. Notes: The results are based on the question ‘What do you think is the percentage likelihood (probability) of the UK leaving the EU, after the end of any transitional arrangements, in each of the following years? ’. Data were collected in January 2020. All values are weighted.

Expected eventual impact of Brexit on sales Average probability (per cent) 60 Feb - Apr 2017 Aug - Oct 2017 Feb - Apr 2018 Aug - Oct 2018 50 Nov 2018 - Jan 2019 Feb - Apr 2019 May - July 2019 40 Aug - Oct 2019 Nov 2019 - Jan 2020 30 20 10 0 Large negative Small negative effect No impact Small positive Large positive effect Source: Decision Maker Panel and authors’ calculations. Notes: The results were based on the question ‘“How likely do you think it is that the eventual agreement will have the following effects, compared to what would have been the case had the UK remained a member of the EU? ” Probability add to 100% across five options: [add 10% or more to sales], [add less than 10% to sales], [make little difference], [subtract less than 10% from sales], [subtract more than 10% from sales]”

Expected eventual impact of Brexit on sales and uncertainty Average probability (per cent) 70 Low uncertainty 60 High uncertainty 50 40 30 20 10 0 Large negative, < 10% Small negative, 10% to 0% No impact Small positive, 0% to 10% Large positive, > 10% Source: Decision Maker Panel and authors’ calculations. Notes: The results were based on the question ‘How much has the result of the EU referendum affected the level of uncertainty affecting your business? ’ and “How likely do you think it is that the eventual agreement will have the following effects, compared to what would have been the case had the UK remained a member of the EU? ” Probability add to 100% across five options: [add 10% or more to sales], [add less than 10% to sales], [make little difference], [subtract less than 10% from sales], [subtract more than 10% from sales]”

Number of hours a week spent by CFOs on preparing for Brexit CFO Percentage of respondents CEO 40 30 20 10 0 None Up to 1 hour 1 -5 hours 6 -10 hours More than 10 hours Source: Decision Maker Panel and authors’ calculations. Notes: The results are based on the question ‘On average, how many hours a week are the CEO and CFO of your business spending on preparing for Brexit at the moment? Please select one option for each for CEO and CFO: None; Up to 1 hour; 1 to 5 hours; 6 to 10 hours; More than 10 hours; Don’t know’. This question was asked between November 2017 and October 2019. Don’t knows are excluded. All values are weighted.

Brexit and investment Net balance of respondents who report having reduced investment due to Brexit (per cent) 25 20 15 10 5 0 Training Software and IT R&D Investment type Machinary, equipment and buildings All Source: Decision Maker Panel and authors’ calculations. Notes: The results are based on the question ‘Could you say how the UK’s decision to vote ‘Leave’ in the EU referendum has affected your capital expenditure since the referendum? Please select one option for each type of investment [Training of employees; Software, data, IT, website; Research and development; Machinery, equipment and buildings]: a large positive influence, adding 5% or more; a minor positive influence, adding less than 5%; no material impact; a minor negative influence, subtracting less than 5%; a large negative influence, subtracting 5% or more. ’ ‘Net balance’ is defined as the share who say that Brexit has reduced investment less the share saying it has increased investment. Data were collected between February and April 2019. All values are weighted.

Impact of the Brexit process on investment, employment and productivity in the three years following the EU referendum Source: Bureau van Dijk FAME dataset, Decision Maker Panel and authors’ calculations. Notes: Results presented here are based on regression analysis and difference-in-difference estimator. Productivity is defined as real value-added (operating profits plus total labour costs divided by the aggregate GDP deflator) per employee using accounting data. Productivity estimates include both within and between-firm effects. Lower productivity estimate allows within-firm effects to vary by firm size, the higher estimate assume the effects are the same for firms of all sizes.