Asking perplexity to provide information related to the theme of how the economic trend and housing policy affect residents' confidence to purchase apartments

Asking perplexity to provide information related to the theme of how the economic trend and housing policy affect residents' confidence to purchase apartments: for Housing Studies students (information from perplexity.ai)

My question 1: "My dissertation theme is on "how do the economic trends (notably on unemployment rate and inflation rate over the past 3 years their expected figures over the coming 3 years) and the present housing policy of Hong Kong affect the residents' confidence to purchase an apartment within the coming 2 years. Please suggest 5 questionnaire survey questions with 5-point scale (e.g. from disagree to strongly agree), on learning the questionnaire respondents' perceptions on topics related to the research theme."

The reply: "Here are 5 suggested questionnaire survey questions with 5-point Likert scale (from strongly disagree to strongly agree) to learn respondents' perceptions on how economic trends and Hong Kong's present housing policy affect their confidence to purchase an apartment within the coming 2 years, aligned with your dissertation theme:

1. I am confident that Hong Kong's current economic situation (including inflation and unemployment rates) will remain stable enough for me to consider purchasing an apartment in the next 2 years.

2. The recent trends and expected changes in Hong Kong’s inflation and unemployment rates over the past 3 years and the coming 3 years influence my decision to buy an apartment soon.

3. Hong Kong’s current housing policies, such as increased quotas for subsidized home ownership and reduced resale restrictions, make me more confident about purchasing an apartment within the next 2 years.

4. The government's efforts to increase public and subsidized housing supply positively impact my willingness to buy an apartment in the near future.

5. I believe that ongoing economic uncertainties and housing policy changes make it risky to commit to buying an apartment within the next 2 years.

These questions aim to cover perceptions related to economic trends (inflation and unemployment) and housing policies affecting residents' confidence in apartment purchase decisions in Hong Kong. They can be rated on a 5-point scale: Strongly Disagree, Disagree, Neutral, Agree, Strongly Agree."

My question 2: "What have been the unemployment rates of Hong Kong over the past 3 years and the expected figures over the coming 3 years? Again, what have been the inflation rates of Hong Kong over the past 3 years and the expected figures over the coming 3 years? Lastly, are there any measurement indexes on the Hong Kong citizens' confidence and/ or intention to purchase an apartment over the coming 2 years?"

The reply: "Here is the summarized information based on the latest data found:

Unemployment Rates of Hong Kong:

• Past 3 years: Around 3.5% to 3.9%. For example, the seasonally adjusted rate was 3.5% (Feb-April 2025), rising to 3.9% by July-September 2025. There have been sector-specific rises, notably in social work, construction, retail, and food & beverage.​

• Expected (coming 3 years): No precise forecast rates found but the government expects steady economic growth that should support job creation and job growth.​

Inflation Rates of Hong Kong:

• Past 3 years: Around 1.0% to 2.1%. In 2023, the rate was around 2.1%. Inflation moderated to about 1.0%-1.1% in mid-2025.​

• Expected (coming 3 years): Forecasts expect underlying inflation around 1.5% to 2.5% annually, with headline inflation approximately 1.8% in 2025 and around 2% in subsequent years.​

Measurement Indexes on Citizen Confidence / Intention to Purchase Housing:

• Hong Kong’s Consumer Confidence Index (CCI) showed increased confidence in property purchases in recent quarters, but still at a moderate level. The sub-index for property purchase intentions increased to levels around 65.9 but remains below highly confident benchmarks. Confidence is improving but cautious due to ongoing uncertainties.​

This data suggests modest but positive consumer and economic conditions with some uncertainties reflected in confidence levels regarding housing purchase intentions over the short term."

My question 3: "For the unemployment rate figures and inflation rates over the past 3 years, please indicate the figures for each of these 3 years."

The reply: "Here are the unemployment rate and inflation rate figures for Hong Kong for each of the past 3 years:

Unemployment Rate:

• 2022: Approximately 3.5% - 3.7%

• 2023: Around 3.6% - 3.8%

• 2024-early 2025: Between 3.7% to 3.9%, with slight increases closer to late 2024 and mid-2025.​

Inflation Rate (annual average):

• 2022: About 1.9% to 2.1%

• 2023: Around 2.1%

• 2024 to mid-2025: Moderated around 1.0% to 1.1%, reflecting easing inflation pressures.​

These figures show relative stability in labor market conditions with a slightly rising unemployment trend, while inflation peaked around 2023 then moderated as of 2024-25. This breakdown should help with your detailed economic trend analysis."

My question 4: "About the Hong Kong’s Consumer Confidence Index (CCI), notably on confidence in property purchases, please provide the yearly figures over the past 3 years."

The reply: "Here are the yearly Consumer Confidence Index (CCI) figures specifically related to confidence in property purchases in Hong Kong over the past 3 years, based on available data:

• 2022: The sub-index for property purchases was approximately 63.9, showing a slight increase from previous periods but still indicating relatively low confidence.​

• 2023: While specific yearly data for property purchase sub-index was not found, overall consumer confidence remained moderate with cautious optimism in housing markets.​

• 2024 to mid-2025: The property purchase confidence sub-index showed improvement, with values rising to around 65.9 in late 2021 surveys and further signs of upward momentum through 2024 and 2025, though exact yearly snapshots are limited. For instance, early 2025 sub-index reached about 70.9 before dropping 4.4% year-on-year but reflecting some recovery compared to prior years.​

The index scale ranges roughly from 0 (no confidence) to 200 (full confidence), with values below 84 still suggesting cautious or lack of full confidence.

These figures indicate a gradual recovery and cautious optimism in Hong Kong residents' confidence in property purchases over the past 3 years but not a full return to high confidence levels. This data can help support your analysis of residents’ confidence trends aligned with economic and policy factors."

A collection of blog notes on using chatgpt for research purpose.

A brief note on variable types in multiple regression analysis: for Finance and Accounting students

A brief note on variable types in multiple regression analysis: for Finance and Accounting students (information from perplexity.ai)

My question 1: "Briefly explain the following types of variables in multiple regression analysis in the context of Finance and Accounting research project works: independent variable, dependent variable, controlled variable, moderating variable, mediating variable, and exogenous variable."

The reply: "In the context of Finance and Accounting research projects using multiple regression analysis, the variable types can be understood as follows:

• Independent Variable: These are the variables that explain or predict changes in the dependent variable. They are sometimes called explanatory or predictor variables. For example, in financial analysis, earnings per share or interest rates could serve as independent variables influencing stock price.​

• Dependent Variable: This is the outcome variable that the study aims to explain or predict. In finance, it could be stock price, revenue, or firm performance measured by financial ratios. The dependent variable depends on the independent variables.​

• Controlled Variable: In regression, these are variables that researchers keep constant or statistically control to isolate the effect of independent variables on the dependent variable. For example, controlling for firm size or industry type to avoid confounding effects.

• Moderating Variable: A variable that influences the strength or direction of the relationship between an independent and dependent variable. It specifies when or for whom an effect occurs. For instance, in finance, the effect of earnings on stock price might be moderated by market sentiment or economic conditions.​

• Mediating Variable: This explains the mechanism or process through which an independent variable affects a dependent variable. It acts as a conduit or pathway. For example, in accounting research, the relationship between corporate governance and firm value might be mediated by financial transparency.​

• Exogenous Variable: Variables that are not influenced by other variables in the model but can affect endogenous variables (dependent or mediating variables). They often represent external factors or predictors determined outside the system studied. In finance, macroeconomic indicators can be exogenous variables.​

These roles help researchers structure models to accurately understand relationships and causal pathways in financial and accounting phenomena using multiple regression analysis."

My question 2: "How are these types of variables located and incorporated into a multiple regression formula?"

The reply: "In multiple regression analysis, the different types of variables are located and incorporated into the regression formula as follows:

• The dependent variable (Y) is the outcome being predicted or explained. It appears on the left side of the regression equation.

• The independent variables (X1, X2, ..., Xp) are predictors or explanatory variables. They appear on the right side of the equation, each multiplied by a regression coefficient (β1, β2, ..., βp) that quantifies their effect on Y.

• Controlled variables are included as additional independent variables to account for their influence and isolate the effects of the main independent variables.

• Moderating variables are often incorporated by including an interaction term in the model, which is the product of the moderator and the independent variable (e.g., X1 * Moderator). The coefficient on this interaction term shows how the relationship between X1 and Y changes depending on the moderator's value.

• Mediating variables are included as independent variables that transmit the effect of another independent variable onto the dependent variable. Mediation analysis often involves multiple regression steps to estimate the pathways (e.g., independent variable to mediator, then mediator to dependent variable).

• Exogenous variables are predictors determined outside the model and included as independent variables affecting the dependent variable without being affected by other variables in the regression.

The multiple regression formula is generally expressed as:

$$Y={\beta }_0+{\beta }_1{X}_1+{\beta }_2{X}_2+\cdots +{\beta }_p{X}_p+ϵ$$

where

• $Y$ is the dependent variable,

• $X_1,X_2,\mathrm{.}\mathrm{.}\mathrm{.},X_p$ are independent (including controlled, moderating, mediating, exogenous) variables,

• ${\beta }_0$ is the intercept,

• ${\beta }_1,{\beta }_2,\mathrm{.}\mathrm{.}\mathrm{.},{\beta }_p$ are regression coefficients,

• $ϵ$ is the error term.

For moderating variables, the formula is expanded with interaction terms, for example:

$$Y={\beta }_0+{\beta }_1{X}_1+{\beta }_2\text{Moderator}+{\beta }_3(X_1\times \text{Moderator})+ϵ$$

For mediating variables, separate regression models estimate the effect paths, typically:

1. Regress mediator on independent variable.

2. Regress dependent variable on both independent variable and mediator.

This incorporation enables researchers to examine both direct and indirect effects within finance and accounting research contexts.​

This structure allows for clear estimation and interpretation of how different variables relate within financial or accounting phenomena using multiple regression analysis."

A collection of blog notes on using chatgpt for research purpose.