News-Driven Household Macroeconomic Expectations: Regional vs. National Telecast Information

Layer 1: Overview

Research question and motivation: The paper asks whether and which television news topics shape French households’ one-year-ahead macroeconomic expectations (inflation, unemployment, economic situation), over and above information already in national statistics, and whether REGIONAL (not just national) news matters. This is important because media are the primary information intermediary between households and the economy, household expectations feed into consumption/spending decisions and thus monetary-policy transmission, and the literature had largely ignored that households’ information sets may depend on local/regional economic conditions.

Data and sample: Monthly data, January 2004 to December 2019. Household expectations come from INSEE’s monthly consumer-confidence survey (~2,000 households interviewed by phone each month, each interviewed three consecutive months). The author uses three qualitative questions (future prices, unemployment, economic situation) to build national and regional “balances of opinions,” plus a quantitative inflation-expectation question (answered on average by only 56% of monthly respondents, which prevents building regional quantitative series). News data come from the French National Audiovisual Institute archives of TF1 and France 2 (national, 8pm newscasts watched daily by roughly 20% of households) and France 3 (7pm regional newscasts). National and regional newscasts discuss roughly 24 and 11 stories per day, respectively. Human archivists assign standardized expert keywords/topics. The author constructs coverage indicators for 73 topics (12 aggregate + 61 socio-economic), selected if discussed in more than 75% of months. Two coverage measures are built: count-based (frequency of stories) and a novel time-based “viewer time exposure” (seconds spent on a topic). Metropolitan France is split into 13 administrative regions (Corsica/overseas excluded).

Empirical strategy: Penalized predictive regressions (LASSO, Tibshirani 1996), following Larsen et al. (2021), with the rigorous data-driven plug-in penalty of Belloni et al. (2012, 2014) and post-LASSO OLS with Newey-West HAC standard errors. News variables are lagged one month (to avoid simultaneity/look-ahead); statistical controls lagged two months (except EPU index and diesel price, lagged one). National statistical controls include 10-year bond yield, CPI, exchange rate, unemployment rate, industrial production, EPU index, diesel price; milk and bread prices added for inflation regressions. Regional regressions are run separately per region adding national plus regional news and three regional controls (job seekers, dwelling permits, business failures). Household-level regressions use OLS (quantitative) and probit (binary) with demographic, year, and region effects.

Main findings (with magnitudes): From 73 candidate topics, 14 are selected, with on average about four topics per regression in addition to statistical series, confirming news carries information not in national statistics. Average inflation expectations are significantly driven by news on energy and taxes; decomposing energy shows OIL news is consistently selected (gas to a lesser extent, not robust to statistics). Future-economic-situation expectations load on purchasing power, living cost, and economic plan; unemployment expectations load negatively on economic crisis and oppositely on economic life. Regional results: both regional AND national labor-market news predict the unemployment balance of opinions; regional lay-off and unemployment topics are consistently selected, and more regional unemployment coverage makes households more pessimistic about NATIONAL unemployment. At the household level, one additional energy story raises the probability of expecting price increases by 0.19% and one additional fiscal-policy story by 0.10%; one additional regional-unemployment story raises the probability of expecting more unemployment by 0.36% (0.33% in panel specification; energy 0.17% and fiscal policy 0.08% in panel). The unemployment balance-of-opinions dispersion across regions averages 24 percentage points. Independent/self-employed workers are most sensitive to regional unemployment news; the effect is weaker for young and below-first-quartile-income households. Implications: news topic fluctuations carry expectation-relevant information complementary to official statistics, regional news reveals a geographical dimension to household attention consistent with endogenous information acquisition / rational inattention, and this matters for using inflation expectations as a monetary-policy tool.

Layer 2: Deep Dive

What is the identification/empirical strategy and what are the main threats to it?

The strategy is predictive: LASSO (with the Belloni et al. rigorous plug-in penalty) selects, from 73 candidate news topics plus statistical controls, those with predictive power for one-year-ahead expectations, followed by post-LASSO OLS with Newey-West HAC standard errors. The paper is explicit that it estimates a predictive relationship, not a structural causal effect. Threats addressed: simultaneity/look-ahead bias is handled by lagging news one month and statistics two months (one for diesel/EPU/milk/bread, which households observe in real time); overfitting and spurious selection are reduced by the data-driven penalty (more parsimonious than cross-validation, robust to heteroscedasticity). A residual threat is that news coverage and expectations could both respond to an unobserved underlying economic state; the author partially addresses this by showing news survives inclusion of official national and regional statistics and that ‘partial adjusted R2’ attributable to news is non-zero.

What are the main mechanisms and how are they distinguished empirically?

The core mechanism is endogenous/limited-capacity information acquisition: households cannot absorb all information and incorporate a subset heard from media intermediaries. Expectation-specificity is the key empirical discriminator: energy/oil and tax/fiscal-policy news affect ONLY inflation expectations; labor-market topics (lay-off, unemployment) affect MAINLY unemployment expectations; broad topics (economic crisis, living cost, economy) affect economic-situation and unemployment expectations. The regional dimension is distinguished by separating France 3 regional newscasts from TF1/France 2 national newscasts and running region-specific LASSO, showing regional labor-market news is selected even after controlling for national news and official regional indicators.

What heterogeneity is documented?

Regional heterogeneity: balances of opinions and news topic coverage vary substantially across the 13 regions (e.g., unemployment balance-of-opinions min-max gap averages 24 pp; lay-off/unemployment air-time differs markedly by region). Sentiment heterogeneity: economic crisis carries negative sentiment, economic life positive, yielding opposite-signed coefficients. Household heterogeneity: by employment sector, independent/self-employed workers are MOST sensitive to regional unemployment news (vs public and private sector employees); the regional-unemployment-news effect is less significant for young households and not significant for those below the first income quartile.

What robustness checks are run?

(1) Count-based vs time-based (‘viewer time exposure’) coverage measures give nearly identical selections and R2; time-based is somewhat more parsimonious and more significant for energy on inflation. (2) Outlier-robust inflation-expectation measures (5%, 10%, 15% trimmed means and the median) preserve the energy/tax/fiscal-policy results. (3) Including perceived inflation as a regressor: it is selected but insignificant and does not change energy/tax results; a separate analysis shows news matter for inflation EXPECTATIONS directly, not via perceptions (the selected topic sets are nearly mutually exclusive). (4) Household-level panel exploiting the up-to-three-month repeated interviews (household fixed-effects / random-effects probit) confirms results (energy 0.17%, fiscal policy 0.08% for prices; regional unemployment 0.33% for unemployment). (5) Energy decomposition by source confirms oil (and lesser gas) drives the energy effect. (6) Bootstrapped confidence intervals and demographic-stability checks address the concern that regional series differences are noise or demographic composition.

How does this paper relate to and differ from closely related prior work?

It builds directly on Larsen et al. (2021), adopting their topic-based LASSO approach, and on Carroll (2003), Doms and Morin (2004), Pfajfar and Santoro (2013), Lamla and Lein (2014), Draeger and Lamla (2017), Ehrmann et al. (2015) on media and expectations. Four novelties distinguish it: (1) it uses TELEVISION content rather than newspaper corpora (television being the main source of household economic information per Blinder-Krueger, Curtin); (2) it separates REGIONAL from national newscasts to identify regional drivers of expectation heterogeneity; (3) it uses HUMAN-EXPERT-assigned topics rather than algorithmic topic models (more accurate for short TV stories, allows distinguishing sub-topics like deficit, lay-off, tax); (4) it adds a time-based ‘viewer time exposure’ coverage measure capturing duration, not just frequency. The regional finding extends Kuchler-Zafar (2019) and Malmendier-Nagel (2016) extrapolation results: households extrapolate not just personal experience but their region’s labor-market experience to national expectations.

What are the policy implications and their scope conditions?

Understanding which news households incorporate is key for using inflation expectations as a monetary-policy tool; energy/oil and tax/fiscal news drive inflation expectations, so central-bank communication and expectation management must account for media salience of these topics. The regional finding implies a geographical dimension to household attention relevant for modeling information frictions (rational inattention, sparsity, sticky information with endogenous updating). Scope conditions: results are predictive (not causal), specific to France 2004-2019, rest on expert-assigned TV topics, and the regional analysis applies to qualitative balances of opinions only (the quantitative inflation question’s 56% response rate prevents regional quantitative series). Whether households OVERWEIGHT local labor markets is explicitly stated to be beyond the paper’s scope.

What other significant findings, extensions, or caveats appear?

Correlations between national and regional news indicators are limited, confirming regional news carries information absent from national news (only country-wide topics like tourism, tax, economic crisis, demonstration, and prices are highly correlated). Regional peaks reflect identifiable local events (the 2013 ‘Red Beanies’ movement and 2016 agricultural crisis in Brittany). Past inflation and official statistics are heavily selected for inflation/price expectations (consistent with Larsen et al.); milk and bread price changes matter for quantitative inflation expectations but not the qualitative price balance, suggesting households extrapolate frequently-bought items for quantitative answers. Electricity is absent from selection despite a larger basket weight than gas, plausibly due to France’s regulated electricity prices. The author notes media exhibit a documented negative-news asymmetry (Soroka 2006), so sentiment-neutral topics tend to carry predominantly negative news.

Key Concepts

Balance of opinions: A monthly index computed as the difference between the share of households expecting one macroeconomic direction and the share expecting the opposite (e.g., for unemployment, share expecting an increase minus share expecting a decrease; for prices, share expecting an increase minus share expecting prices to stay the same, since households rarely expect deflation). Used as the qualitative expectation measure at national and regional levels.

Viewer time exposure: The paper’s novel time-based coverage measure: the monthly number of seconds viewers are exposed to a given news topic, as opposed to the count-based measure (number of stories). It captures both frequency and duration, reflecting the importance given to a story and its effect on viewer recall.

Expert-assigned topics: News topics assigned by trained archivists of the French National Audiovisual Institute using a standardized grid (relying on title, image, and sound), rather than algorithmic topic models. The author argues these are more accurate for short TV stories and allow distinguishing specialized sub-topics (deficit, lay-off, unemployment) that algorithms would pool.

Endogenous information acquisition: Used in the paper’s own sense as the theoretical frame in which households with limited capacity to acquire/process information choose what to attend to based on expected benefits — invoked to explain why households incorporate regional labor-market news (believing they are more affected by local conditions). Linked to rational inattention, sparsity, and sticky-information models.

Rigorous (plug-in) LASSO penalty: The data-driven penalty of Belloni et al. (2012, 2014) for choosing the LASSO regularization parameter, preferred over cross-validation because it yields a more parsimonious variable selection, lowers overfitting, and is robust to heteroscedasticity; followed by post-LASSO OLS with Newey-West HAC standard errors.

Geographical dimension of attention: The paper’s term for its central regional finding: households’ information collection and attention have a spatial structure, whereby they incorporate regional news (especially on local lay-offs and unemployment) into their NATIONAL expectations, producing geographical heterogeneity in aggregate beliefs.